BDTD - Biblioteca Digital de Teses e Dissertações

URI Permanente desta comunidadehttps://repositorio.ufpa.br/handle/2011/2289

Biblioteca Digital de Teses e Dissertações da UFPA (BDTD). Sistema Eletrônico de Teses e Dissertações (TEDE). Projeto BDTD/UFPA e Instituto Brasileiro de Informação em Ciência e Tecnologia (IBICT).

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Agora exibindo 1 - 20 de 727

Acesso aberto (Open Access)
5G MIMO and LIDAR data for machine learning: mmWave beam-selection using deep learning
(Universidade Federal do Pará, 2019-08-29) DIAS, Marcus Vinicius de Oliveira; KLAUTAU JÚNIOR, Aldebaro Barreto da Rocha; http://lattes.cnpq.br/1596629769697284
Modern communication systems can exploit the increasing number of sensor data currently used in advanced equipment and reduce the overhead associated with link configuration. Also, the increasing complexity of networks suggests that machine learning (ML), such as deep neural networks, can effectively improve 5G technologies. The lack of large datasets make harder to investigate the application of deep learning in wireless communication. This work presents a simulation methodology (RayMobTime) that combines a vehicle traffic simulation (SUMO) with a ray-tracing simulator (Remcom’s Wireless InSite), to generate channels that represents realistic 5G scenarios, as well as the creation of LIDAR sensor data (via Blensor). The created dataset is utilized to investigate beam-selection techniques on vehicle-to-infrastructure using millimeter waves on different architectures, such as distributed architecture (usage of the information of only a selected vehicle, and processing of data on the vehicle) and centralized architectures (usage of all present information provided by the sensors in a given moment, processing at the base station). The results indicate that deep convolutional neural networks can be utilized to select beams under a top-M classification framework. It also shows that a distributed LIDAR-based architecture provides robust performance irrespective of car penetration rate, outperforming other architectures, as well as can be used to detect line-of-sight (LOS) with reasonable accuracy.
Acesso aberto (Open Access)
Abordagem de leitura de texto em imagens provenientes de redes sociais para ganho em disponibilidade de dados
(Universidade Federal do Pará, 2017-10-19) FERREIRA NETO, Luiz Cortinhas; SANTANA, Ádamo Lima de; http://lattes.cnpq.br/4073088744952858
This work aims to propose a methodological adaptation in the process of social network analisys, based on the inclusion of text extracted from images that are obtained from the social networks themselves. Highly important for market intelligence, product analysis, CRM and SCRM processes, since these are market trends used by large companies, thus, promotes financial and research incentives. The adaptation proposed in here has its importance based on data availability, which has become increasingly restricted, thanks to the use of APIs, interfaces of data access management where, in several different ways, each social network limits the data query, either by type of data, quantity or collected window. This research intends to prove, through case studies, that there is relevant information gain to sentiment analyses process when textual data derived from images are used.
Acesso aberto (Open Access)
Uma abordagem híbrida e semiautomática para estimativa de regiões cobertas por nuvens e sombras em imagens de satélite: análise e avaliação
(Universidade Federal do Pará, 2014-03-31) SOUSA, Danilo Frazão; PELAES, Evaldo Gonçalves; http://lattes.cnpq.br/0255430734381362
The main goals of this work are to propose a more automatic and efficient algorithm to replace regions of clouds and shadows in satellite images as well as an index of reliability that is previously applied to each image, in order to measure the feasibility of the estimation of the regions covered by atmospheric components using that algorithm. The motivation comes from the problems caused by these atmospheric elements, among them: to impede the identification of objects of the image, to make the urban and environmental monitoring more difficult, and to interfere in crucial stages of digital image processing to extract information for the user, such as segmentation and classification. Through a hybrid approach is proposed a method for decomposing regions using a median non-linear low-pass filter, in order to map the regions of structure (homogeneous) and texture (heterogeneous) in the image. In these areas was applied restoration methods Inpainting by Smoothing based on Discrete Cosine Transform (DCT), and Exemplar-Based Texture Synthesis, respectively. It's important to note that the techniques have been modified to be able to work with images obtained through of satellite sensors with peculiar features such as large size and/or high spectral variation. Regarding to the reliability index, it aims to analyze the image that contains atmospheric interference and hence estimate how much reliable will be the redefinition, based on the percentage of cloud cover over the regions of texture and structure. This index is composed by combining the result of supervised and unsupervised algorithms involving three metrics: Average of Accuracy Global, Measure Of Structural Similarity (SSIM) and Average of Pixels Confidence. Finally, it was verified the effectiveness of these methods through a quantitative assessment (provided by the index) and qualitative (the images resulting from processing), showing the possible application of the techniques to solve the problems that motivated this work.
Acesso aberto (Open Access)
Abordagem Inteligente com Combinação de Características Estruturais para Detecção de Novas Famílias de Ransomware
(Universidade Federal do Pará, 2024-03-22) MOREIRA, Caio Carvalho; SALES JUNIOR, Claudomiro de Souza de; País de Nacionalidade Brasi
Ransomware is a malicious software that aims to encrypt user files and demand a ransom to unlock them. It is a cyber threat that can cause significant financial damage, as well as compromise privacy and data integrity. Although signature-based detection scanners commonly combat this threat, they fail to identify unknown ransomware families (variants). One method to detect new threats without the need to execute them is static analysis, which inspects the code and structure of the software, along with classification through intelligent approaches. The Detection of New Ransomware Families (DNFR) can be evaluated in a realistic and challenging scenario by categorizing and isolating families for training and testing. Hence, this thesis aims to develop an effective static analysis model for DNFR, which can be applied in Windows systems as an additional security layer to check executable files upon receipt or before execution. Early ransomware detection is essential to reduce the likelihood of a successful attack. The proposed approach comprehensively analyzes executable binaries, extracting and combining various structural features, and distinguishes them between ransomware or benign software employing a soft voting model comprising three machine learning techniques: Logistic Regression (LR), Random Forest (RF), and eXtreme Gradient Boosting (XGB). Results for DNFR demonstrated an average accuracy of 97.53%, precision of 96.36%, recall of 97.52%, and F-measure of 96.41%. Additionally, scanning and predicting individual samples took an average of 0.37 seconds. This performance indicates success in quickly identifying unknown ransomware variants and adapting the model to the constantly evolving landscape, suggesting its applicability in antivirus protection systems, even on resource-limited devices. Therefore, the method offers significant advantages and can assist developers of ransomware detection systems in creating more resilient, reliable, and fast-response solutions.
Acesso aberto (Open Access)
Abordagem para o desenvolvimento de um etiquetador de alta acurácia para o Português do Brasil
(Universidade Federal do Pará, 2011-10-21) DOMINGUES, Miriam Lúcia Campos Serra; FAVERO, Eloi Luiz; http://lattes.cnpq.br/1497269209026542
Part-of-speech tagging is a basic task required by many applications of natural language processing, such as parsing and machine translation, and by applications of speech processing, for example, speech synthesis. This task consists of tagging words in a sentence with their grammatical categories. Although these applications require taggers with greater precision, the state of the art taggers still achieved accuracy of 96 to 97%. In this thesis, corpus and software resources are investigated for the development of a tagger with accuracy above of that of the state of the art for the Brazilian Portuguese language. Based on a hybrid solution that combines probabilistic tagging with rule-based tagging, the proposed thesis focuses on an exploratory study on the tagging method, size, quality, tag set, and the textual genre of the corpora available for training and testing, and evaluates the disambiguation of new or out-of-vocabulary words found in texts to be tagged. Four corpora were used in experiments: CETENFolha, Bosque CF 7.4, Mac-Morpho, and Selva Científica. The proposed tagging model was based on the use of the method of transformation-based learning (TBL) to which were added three strategies combined in a architecture that integrates the outputs (tagged texts) of two free tools, Treetagger and -TBL, with the modules that were added to the model. In the tagger model trained with Mac-Morpho corpus of journalistic genre, tagging accuracy rates of 98.05% on Mac-Morpho test set and 98.27% on Bosque CF 7.4 were achieved, both of journalistic genres. The performance of the proposed hybrid model tagger was also evaluated in the texts of Selva Científica Corpus, of the scientific genre. Needs of adjustments in the tagger and in corpora were identified and, as result, accuracy rates of 98.07% in Selva Científica, 98.06% in the text set of Mac-Morpho, and 98.30% in the texts of the Bosque CF 7.4 have been achieved. These results are significant because the accuracy rates achieved are higher than those of the state of the art, thus validating the proposed model to obtain a more reliable part-of-speech tagger.
Acesso aberto (Open Access)
Uma abordagem para otimização do período de sensoriamento em rádio cognitivo com algoritmo genético multiobjetivo
(Universidade Federal do Pará, 2011-08-25) YOSHIOKA, Peterson Marcelo Santos; COSTA JÚNIOR, Carlos Tavares da; http://lattes.cnpq.br/6328549183075122
The spectral efficiency in networks based on cognitive radio (CR) technology can be compromised if the radio is used for a long time for the detection instead of data transmission. So it becomes necessary sensing schemes that have the purpose of obtaining the maximum possible use of spectrum, avoiding unnecessary sensing, as well as obtaining a minimum of interference in the transmission of the primary user due to incorrect detection of its transmission. In this paper, we propose the use of genetic algorithms for the adaptation of the sensing period. The goal is to obtain an optimal channels sensing period in order to maximize the discovery of spectrum opportunities and minimize the overhead due to the sensing. Most related works to this issue adopt fixed sensing overhead, not taking into account that some channels may have less tolerance to interference than others. The proposal presented in this work can adapt to the requirements of tolerance to interference with licensed channel by determining a period of sensing that optimizes the opportunities for any set amount of overhead. Our proposal achieves a gain up to 90% compared to nonoptimized techniques in terms of the number of opportunities found up to 40.9% gain in useful transmission and obtained a reduction in the time of interference of 66.83%. In addition, our proposal also achieves similar results to those obtained by an optimized proposal in the literature, with the advantage of allowing the adaptation of the sensing overhead.
Acesso aberto (Open Access)
Abordagem probabilística para caracterização do sistema de marcação de sequenciamento multiplex na plataforma ABI SOLID
(Universidade Federal do Pará, 2011-07-01) LOBATO, Fábio Manoel França; SANTANA, Ádamo Lima de; http://lattes.cnpq.br/4073088744952858
The next generation sequencers such as Illumina and SOLiD platforms generate a large amount of data, commonly above 10 Gigabytes of text files. Particularly, the SOLiD platform allows the sequencing of multiple samples in a single run (called multiplex run) through a marking system called Barcode. This feature requires a computational process for separation of data per sample, therefore, the sequencer provides a mixture of all samples in a single output. This process must be secure to avoid any harm that may scramble further analysis. In this context, this dissertation proposes development of a probabilistic model capable of characterizing the marking system used in multiplex sequencing. The results corroborate the adequacy of the model obtained, which allows, among other things, identify faults in some step in the sequencing process, adapt and develop new protocols for sample preparation, and assign a grade to the reliability of data generated and guide a filtering process that respects the characteristics of each sequence, without discarding sequences useful in an arbitrary manner.
Acesso aberto (Open Access)
Uma abordagem SDN para virtualização de redes
(Universidade Federal do Pará, 2016-11-25) PINHEIRO, Billy Anderson; ABELÉM, Antônio Jorge Gomes; http://lattes.cnpq.br/5376253015721742
The virtual SDN networks (vSDNs) have emerged from the association of virtualization and Software-Dened Networking (SDN), providing greater control and better use of network resources. Several studies have already shown the feasibility and benets of this approach. However, the issue still lacks solutions that can virtualize a network in a scalable, intuitive and simplied manner. Thus, this thesis proposes an SDN approach to network virtualization with the aim of reducing the limitations on vSDNs. Therefore, it is suggested to adopt in network virtualization the separation between data plans (distributed) and control (centralized), the global network view and use of ow abstraction to manage the communication between the dierent points. To support our proposition, three solutions were developed: the CIM-SDN (Common Information Model for Software-Dened Networking), to enable the use of formal representation of the new elements of vSDNs; The NVP (Network Virtualization Proxy), to provide greater scalability by separating the control plane into centralized and decentralized parts; And Graph Virtualization Layer (GVL), to provide greater use of abstractions between the hypervisor and controllers, thereby simplifying the understanding and use of the network. Proof of concept tests was carried out for the three proposed solutions, demonstrating the feasibility of the approach.
Acesso aberto (Open Access)
Acionamento vetorial por controlador fuzzy modo deslizante de motor de indução
(Universidade Federal do Pará, 2010-05-20) TEIXEIRA, Raphael Barros; BARRA JUNIOR, Walter; http://lattes.cnpq.br/0492699174212608; BARREIROS, José Augusto Lima; http://lattes.cnpq.br/1246564618922453
This work studies the technique of vector drive applied to three-phase induction motor (IM), using as the control strategy fuzzy control and sliding mode control in a setting here called Fuzzy Sliding Mode Controller (FSMC) . A dynamic model is developed at IM in variable ’d - q’ which led to an electromechanical model state space that exhibits strong nonlinearities . In this model the conditions that allow vector control decouple the torque and flux at IM, so that their dynamic behavior is similar to that observed in a DC machine are applied. In this condition, the proportional and integral type (PI) controllers are implemented to control motor speed and current loops, and computational simulations for tracking speed and load disturbance are carried out, which lead to satisfactory results from the point of view dynamic. In order to investigate the performance of nonlinear strategies in this approach the study of control technique the switching structure of the sliding mode type is displayed. A conventional sliding mode controller is implemented, where it appears that, despite the excellent dynamic performance of the occurrence of the phenomenon of ”chettering”precludes the application of this strategy in actual tests. Thus, FSMC control strategy is proposed, trying to associate the good result obtained with the dynamic sliding mode controller and the suppression of the chettering, which is achieved by defining a layer switching fuzzy type. The FSMC proposed controller is subjected to the same computational tests that the PI controller, leading to superior results to the latter the transient dynamic response, but with the presence of steady-state error. To attack this problem is implemented one of the strategies Fuzzy FSMC combination with the action of PI control, where the first seeks to operate in remote regions of the switching surface and the second seeks to introduce the effect of integral action near the surface. The results show the feasibility of the strategy in variable speed drive that demand high dynamic performance.
Acesso aberto (Open Access)
Ações de eficiência energética em navios: estudo de caso e um navio patrulha da Marinha do Brasil
(Universidade Federal do Pará, 2016-08-26) AQUINO, Suzane Cruz de; MORAES, Hito Braga de; http://lattes.cnpq.br/5044859479302394; TOSTES, Maria Emília de Lima; http://lattes.cnpq.br/4197618044519148
Due to growing concern about the environment, the IMO (International Maritime Organization), through MARPOL (International Convention for the Prevention of Pollution from Ships), has developed the first mandatory regulation of the area about the energy efficiency of ships aiming the reduction of greenhouse gases emissions and costs related to energy consumption. This dissertation proposes a methodology of energy efficiency measures in a patrol ship of the Navy of Brazil. The analyzed ship, the P-49 or Guarujá, is a 19 years old vessel just as almost all its equipments. The Guarujá is electrically a isolated propulsion system from the power generation, then the target of this research were those systems with the highest electricity demand: the lighting system, cooling, electric power generation, saving and cold storages. However, the information available above those systems have proven scarce, thus it was exploited only the bulbs and some compressors and fan motors. The actions proposed to equipment available verification were 1. the exchange of the reference case bulbs with LED lamps; and 2. replacing the engines with similar specimens of higher yield. They were analyzed financially and environmentally by RETScreen software, an important tool for energy efficiency and renewable sources studies developed by the Government of Canada; with the aid of PROCEL simulator, BD Motor, promoting greater focus on the engines due to its complexity and significance in the optimal functioning of the ship's systems. The actions proved viable, with the total turnaround time of two years, reducing emissions by 164 tCO2 in 20 years and saving about R$ 352,974.80 at the end of the project time, thus justifying their implementation.
Acesso aberto (Open Access)
Acompanhamento e avaliação de projetos através da monitoração de eventos em um ambiente de gestão de processos de software
(Universidade Federal do Pará, 2007-07-04) PAXIÚBA, Carla Marina Costa; REIS, Rodrigo Quites; http://lattes.cnpq.br/9839778710074372
One of the greatest challenges found in software project management nowadays is to know the true dimension of what is being managed. There are several concerns that are relevant to project managers with respect to the estimation of size, duration, and cost of a project. In this context researchs show that the minor part of the projects are completed on time, on budget, and with all the features and functions originally specified. The other projects are completed overbudget, late or fail. Software project and product management can reach a given level of efficacy and exactness only if certain measurements are made in order to make it possible to manage based on facts. This dissertation focuses on efficient project management process which must be guided by the international process improvement standards and through the use of metrics as a fundamental tool for an effective project management. The basic assumption is that, without the use of adequate metrics, the planning and monitoring of projects become empirical activities, based solely on the feeling and experience of the project manager. This work presents a proposal for projects monitoring through the extension of the event recording mechanism of the WebAPSEE process-centered software engineering environment. The mechanism is the base to provide software support to generate monitoring reports based on process improvement approaches like CMMI and the Brazilian MPS.BR. The proposal was evaluated through a critical analysis involving the monitoring of simulated project with the proposed tool.
Acesso aberto (Open Access)
Acoplamento de modos guiados em cabos de pares trançados utilizando antenas com simetria radial no cenário terabit DSL
(Universidade Federal do Pará, 2020-03-26) SOUSA, Brenda Penedo Tavares de; COSTA, João Crisóstomo Weyl Albuquerque; http://lattes.cnpq.br/9622051867672434
The development of data transmission standards and access technologies has always been linked to the need to supply high data rates. Thus, technologies already implemented, such as the DSL (Digital Subscriber Line) system that uses twisted pairs for transmission, have been adjusting to support this growing data demand. In DSL systems, the twisted pairs are used as a transmission line, using the transverse electromagnetic mode (TEM). However, the physical limitations of the twisted pair as a transmission line prevent the system from achieving higher rates, needed to support fifth generation (5G) applications. Recently, it was proposed to use other transmission modes in the twisted pair, the higher order guided modes, as an alternative for this structure to be able to support transmission rates of the order of Terabits per second, having been termed as the Terabit DSL technology (TDSL). However, one of the challenges for this implementation is the coupling of the guided modes in the twisted pair, since they are not widely explored in the context of the propagation of higher-order guided modes, as simpler waveguides, such as Sommerfeld and Goubau. In this scenario, this dissertation aims to evaluate the coupling of the radiated signal between an antenna with radial propagation and the twisted pair cable, analyzing the electromagnetic behavior of structures. Considering that the twisted pair cable does not have a closed analytical model for the behavior of higher order modes, which propagate along these structures, all the results were obtained from numerical simulations in the software HFSS (High Frequency Structure Simulator).These results are in terms of the scattering parameter of the antenna and the electromagnetic field in the cable, making it possible to evaluate the coupling efficiency, the signal guidance and to predict the transmission rate available to users. The results obtained showed that the coupling between the antenna and the unshielded twisted pair cable reached levels of up to 83.83 % at frequencies of 0.15 THz, demonstrating a high coupling efficiency when compared to simpler scenarios in the literature, reaching levels on average 67 %. It was found that the use of these cables for data transmission is effective, managing to deliver rates of up to 1.737 Tbps in cables of up to 10 meters, while the rate forecasts for the TDSL scenario that consider the 100 % coupling reach levels of 2.013 Tbps.
Acesso aberto (Open Access)
Adequação do laboratório de alta tensão da UFPA - LEAT aos requisitos gerais para a competência de laboratórios de ensaio e calibração da norma ABNT NBR ISO/IEC 17025
(Universidade Federal do Pará, 2022-02-24) BRASIL, Alexandre de Souza; NUNES, Marcus Vinícius Alves; http://lattes.cnpq.br/9533143193581447
Phenomena that cause electrical imbalances in power systems occur constantly, which generates the need to study them in order to allow the development of electrical networks and equipment that behave more reliably and robustly in the face of such disturbances. These studies are generally carried out in specialized High Voltage and High Power laboratories. Over the years, the market started to demand that these studies also provide results that comply with quality standards certified by official bodies. In this sense, this dissertation aims to propose the necessary adaptation of the High and Extra High Voltage Laboratory of the Federal University of Pará (LEAT) to the requirements for the competence of testing and calibration laboratories defined by the ABNT NBR ISO/IEC 17025 standard, with a focus on development and implementation a Quality Management System; creation of operational procedures and safety guidelines; establishment of a calibration program for laboratory equipment; and identification of motivations, advantages and impacts related to the implementation of the requirements of that standard, as well as the difficulties and solutions found. For this, first, a literary survey was carried out that sought to know the national panorama of higher education institutions with accredited laboratories under the referred standard. Then, the process of implementing the requirements of the standard began, which was based on the methodology adapted from Grochau (2011). Finally, the lived experience allowed us to observe that the adaptation to the standard requirements in laboratories linked to public institutions, although complex at first, is fully capable of providing several benefits and advantages, as long as the peculiarities of this type of institution are respected, such as: bureaucracy; resource limitation; training of the personnel involved and; reconciling research and teaching activities with services provision.
Acesso aberto (Open Access)
Agrupamento de fornos de redução de alumínio utilizando os algoritmos Affinity Propagation, Mapa auto–organizável de Kohonen (som), Fuzzy C–Means e K–Means
(Universidade Federal do Pará, 2017-10-11) LIMA, Flávia Ayana Nascimento de; CARDOSO, Diego Lisboa; http://lattes.cnpq.br/0507944343674734; OLIVEIRA, Roberto Célio Limão de; http://lattes.cnpq.br/4497607460894318
The continuous development of technology accounts for measures that provide industries benefits to grant them profitability and competitive advantage. In the mineralogy field, aluminum smelting usually requires substantial number of cells, also known as reduction pots, to produce aluminum in a continuous and complex process. Analytical monitoring is essential for those industries’ competitive advantage, given that during operation some cells show behavior similar to others, thereby forming clusters of cells. These clusters depend on data patterns usually implicit or invisible for the operation, but can be found by data analysis techniques. In this work four clustering techniques are presented to that end: the Affinity Propagation; the Kohonen Self Organizing Map; the Fuzzy C–Means; and the K–Means Algorithm. These techniques are used to find and group cells that share similar behavior, by analysing seven variables which are closely related to the aluminum reduction process. This work aims at addressing the benefits of clustering, especially by simplifying the aluminum potline analysis, once a large group of cells might be summarized in one sole group, what can provide more compact yet rich information for data driven modeling and control. Moreover, the identification of similar data patterns in clusters makes the task of those who is going to be in charge of analyzing these dats. This work also identifies the ideal cluster size for each technique applied.
Acesso aberto (Open Access)
Algoritmo de Sleep Mode para redes LTE em conectividade dual
(Universidade Federal do Pará, 2015-09-18) ARAUJO, Ivanes Lian Costa; KLAUTAU JÚNIOR, Aldebaro Barreto da Rocha; http://lattes.cnpq.br/1596629769697284
This work presents the analysis of the benefits of dual connectivity in Long Term Evo- lution (LTE) networks, and proposes a sleep mode algorithm in order to increase even more the network efficiency. Among the sleep mode algorithms for dual connectivity in literature, none makes an approach regarding the small cells backhaul capacity for the activation decision of these small cells. The lack of an appropriate sleep mode process that takes backhaul issues into consideration can lead to network bottlenecks, greater latency and packet drops. For this reason, the algorithm highlights relevant aspects in LTE networks, and quantifies the benefits obtained not only by the use of the algorithm but also by the use of the dual connectivity itself. To accomplish this goal, several simulations were performed with the software Riverbed Mode- ler, based on 3rd Generation Partnership Project (3GPP) parameters and papers from this area. The simulation results show that lower delay levels can be achieved with the use of dual con- nectivity, and even lower results can be obtained with the use of the proposed algorithm, which also contributes to a more energy efficient usage of network resources. Furthermore, results regarding backhaul traffic in the core network and among small cells are also analyzed. The results, in general, show several advantages of dual connectivity and the proposed algorithm in LTE networks.
Acesso aberto (Open Access)
Algoritmo genético com interação social nebulosa
(Universidade Federal do Pará, 2012-04-19) TEIXEIRA, Otávio Noura; OLIVEIRA, Roberto Célio Limão de; http://lattes.cnpq.br/4497607460894318
This work presents a new new hybrid metaheuristic and bioinspired in nature, based on three main pillars, namely: Genetic Algorithms; Game Theory; and Fuzzy Logic. Thus, the Fuzzy Social Interaction Genetic Algorithm , or F-SIGA, is based and characterized by allowing individuals in the population the possibility to participate in the Social Interaction process. This step is prior to the selection process for the generation of offspring, and in it they can make gains through disputes with other individuals. For this, each individual is characterized by two chromosomes, one related to solving the problem in question; and, the other, with the gene encoding a behavioral strategy. As disputes environment is used the Prisoner's Dilemma game, in 2-person and N-person versions, including the fuzzy approach. In addition, individuals are evaluated by a fitness function that includes: a representation of the problem´ solution, the gains made in disputes and also the experience factor, using the experience acquired by the individual as well as a component to assist in the evolving process of the population. This characteristic gave rise to the ESIA algorithm - not originally planned - where only the information obtained from social interactions are considered in the selection of individuals for reproduction stage. Methodologically, the work evolved into the emergence of the ESIA algorithm, which is a new class of Evolutionary Algorithms based on social interaction. Thus, this work presents four algorithms: SIGA, NpSIGA, F-SIGA and ESIA, with its theoretical foundations and also practical results of applying them to global optimization problems with and without constraints; and the instances of the Travelling Salesman Problem.
Acesso aberto (Open Access)
Algoritmo genético retroviral iterativo
(Universidade Federal do Pará, 2010-09-10) MOREIRA, Renato Simões; AFFONSO, Carolina de Mattos; http://lattes.cnpq.br/2228901515752720
This work presents the development of a hybrid meta-heuristic based on the viral life cycle, specifically from Retroviruses, which are part of nature’s swiftest forms. This algorithm is called Retroviral Iterative Genetic Algorithm (RIGA) and uses as computational basement Genetic Algorithm (GA) and biological basement retroviral replication characteristics, which provides a great diversity increasing the probability to find the solution, what is confirmed by better results obtained by AGRI than AG.
Acesso aberto (Open Access)
Algoritmo memético cultural para otimização de problemas de variáveis reais
(Universidade Federal do Pará, 2019-03-29) FREITAS, Carlos Alberto Oliveira de; SILVA, Deam James Azevedo da; http://lattes.cnpq.br/8540875293894747; OLIVEIRA, Roberto Célio Limão de; http://lattes.cnpq.br/4497607460894318
Technology has made great strides in recent years, but computing resources for certain applications need optimization so that the costs involved in solving some problems are not high. There is a very broad area of research for the development of efficient algorithms for multimodal optimization problems. In the last two decades the use of evolutionary algorithms in multimodal optimization has been shown to be a success. Among these evolutionary algorithms, which are global search algorithms, one can cite the use of Cultural Algorithms. A natural enhancement of the Cultural Algorithm is its hybridization with some other local search algorithm, so as to have the advantages of global search combined with local search. However, the local search Cultural Algorithms used for multimodal optimization are not always evaluated by efficient statistical tests. The objective of this work is to analyze the behavior of the Cultural Algorithm, with populations evolved by the Genetic Algorithm, when the local search heuristics are used: Tabu Search, Beam Search, Climbing and Simulated Annealing. One of the contributions of this work was the updating of the topographic knowledge of the cultural algorithm by the use of the triangular area defined by the best results found in the local search. To perform the analysis, a memetic algorithm was developed by hybridizing the cultural algorithm with the local search heuristics mentioned, being selected one at a time. Real world problems usually have multimodal characteristics, so the evaluations were performed using multimodal benchmark functions, which had their results evaluated by non-parametric tests. In addition, the memetic algorithm was tested on real optimization problems with constraints in the engineering areas. In the evaluations carried out, the developed Cultural Algorithm presented better results when compared to the available results of the researched scientific literature.
Acesso aberto (Open Access)
Algoritmos culturais com abordagem memética e multipopulacional aplicados a problemas de otimização
(Universidade Federal do Pará, 2012-04-20) SILVA, Deam James Azevedo da; OLIVEIRA, Roberto Célio Limão de; http://lattes.cnpq.br/4497607460894318
In many optimization problems is hard to reach a good result or a result close to the optimum value in a feasible time, especially when working on large scale. So, many of these problems are addressed by heuristics or metaheuristics running search for better solutions within the defined search space. Within the natural computing algorithms there are the cultural and genetic algorithms. These are evolutionary metaheuristics complement each other due to the dual mechanism of cultural heritage/genetic. The purpose of this paper is to study and use such mechanisms adding local search heuristics and multipopulation applied to combinatorial optimization problems (knapsack and travel salesman problems), constrained problems and multimodal functions. Some experiments have been conducted to assess the performance of the proposed combination of meta-heuristisc and heuristics mechanisms against approaches found in literature as applied to problem addressed here.
Acesso aberto (Open Access)
Alocação de dois níveis para uma arquitetura h-cran baseada em offloading
(Universidade Federal do Pará, 2019-01-24) GONÇALVES, Mariane de Paula da Silva; BARROS, Fabrício José Brito; http://lattes.cnpq.br/9758585938727609; CARDOSO, Diego Lisboa; http://lattes.cnpq.br/0507944343674734
The accelerated data and apps growth represents significant challenges to the next generation of mobile networks. Amongst them, it is highlighted the necessity for a co-existence of new and old patterns during the transition of architectures. Thus, this paper has investigated solutions for offloading into a hybrid architecture, also known as H-CRAN (Heterogeneous Cloud Radio Access Network Architecture), that centralizes processing and searches a better use of the network resources. The strategy of optimization was analyzed through the evolutive algorithm PSO (Particle Swarm Optimization), in order to find a suboptimal solution to the allocation of two levels (TLA) in the H-CRAN architecture and another one based on FIFO (First In, First Out), for benchmarking purposes. SNR (Noise Interference Signal) average, Maximum Bit Rate, the number of users with or without connections and number of connections in RRHs and macro were used as performance measurements. Through the results, it was noticed an improvement of approximately 60% in the Maximum Bit Rate when compared to the traditional approach, enabling a better service to the users.