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Congress on Evolutionary Computation

作者： Leandro dos Santos Coelho Helon V. H. Ayala Roberto Zanetti Freire Industrial and Systems Engineering Pontifical Catholic University of Parana Curitiba Parana Brazil Graduate Program-PPGEPS Department of Electrical Engineering-DEE PPGEE Federal University of Parana Curitiba Parana Brazil Industrial and Systems Engineering Graduate Program-PPGEPS Pontifical Catholic University of Parana Curitiba Parana Brazil

ISBN: (纸本)9781479904532

Differential evolution (DE) is an evolutionary algorithm (EA) that uses a rather greedy and less stochastic approach to solve optimization problems than other evolutionary methods [1]. Like other EAs, DE is a population-based, stochastic global optimizer, capable of working reliably in nonlinear and multimodal environments. Due to several features such as simplicity, efficiency and global search capabilities, DE rapidly became a successful paradigm of evolutionary computation. However, to achieve adequate performance with DE, the process of tuning the control parameters is essential as its performance is sensitive to the choice of both mutation and crossover settings. This paper proposes a DE algorithm with adaptive tuning of scaling factor (F), crossover rate (CR) and quasi-oppositional probability based on population's variance information - Adaptive Differential Evolution (ADE). Furthermore, ADE adopts a vector called Fm in each dimension of the optimization problem instead of single variable for F as presented in the classical DE approach. The proposed optimization method is validated on the test-bed proposed for the IEEE CEC'13 (IEEE Congress on Evolutionary Computation 2013) contest for real parameter single objective optimization with 28 benchmark functions. Simulation results over the benchmark functions demonstrate the effectiveness and usefulness of the proposed ADE method. This version of paper includes the ADE's performance on the 10, 30 and 50-dimensional benchmark functions.

关键词： Optimization Sociology Statistics Vectors Benchmark testing Evolutionary computation Frequency modulation

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On Efficient Processing of Queries for Live Multi-Streaming Soiree Organization

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IEEE Transactions on Services computing 2023年第4期16卷 2812-2826页

作者： Kankeu Fotsing, C.P. Shen, Chih-Ya Huang, Liang-Hao Chen, Yi-Shin Lee, Wang-Chien Yang, De-Nian International Graduate Program Academia Sinica Social Networks and Human-Centered Computing Program Taipei115 Taiwan National Tsing Hua University Institute of Information Systems and Applications Hsinchu300 Taiwan National Tsing Hua University Department of Computer Science Hsinchu300 Taiwan Academia Sinica Institute of Information Science Taipei115 Taiwan Pennsylvania State University Department of Computer Science and Engineering State CollegePA16801 United States

Real-time social interactions and multi-streaming are two critical features of live streaming services. In this paper, we formulate a new fundamental service query, Social-aware Diverse and Preferred Organization Query (SDSQ), that jointly selects a set of diverse and preferred live streaming channels and a group of socially tight viewers for organization of a live multi-streaming soiree. We prove that SDSQ is NP-hard and inapproximable within any factor, and design SDSSel, a 2-approximation algorithm with a guaranteed error bound. Moreover, we study SDSQ-T, a special case of SDSQ, where the social graph is a threshold graph, and propose TDSSel, a 2-approximation algorithm without any error to SDSQ-T. We propose two pruning strategies, PCP and CDP to boost SDSSel and TDSSel. We further propose a more challenging but practical service query, Generalized Social-aware Maximum Preferred and Diverse Query (GSPQ), a generalization of SDSQ. We design GPDSel, a 4-approximation algorithm for GSPQ with a guaranteed error bound. We propose a strategy to improve the approximation ratios of the proposed algorithms. A user study on Twitch validates SDSQ, and the large-scale experiments on real datasets demonstrate the superiority of the proposed algorithms over several baselines for live-streaming services. © 2008-2012 IEEE.

关键词： Approximation algorithms

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Space and Time Efficiency Analysis of Data-Driven Methods Applied to Embedded systems

Space and Time Efficiency Analysis of Data-Driven Methods Ap...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Iron Tessaro Roberto Zanetti Freire Viviana Cocco Mariani Leandro dos Santos Coelho Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Parana (PUCPR) Curitiba Brazil Mechanical Engineering Graduate Program (PPGEM) Pontifical Catholic University of Parana (PUCPR) Curitiba Brazil

ISBN: (纸本)9781728190495

One of the applications of data-driven methods in the industry is the creation of real-time, embedded measurements, whether to monitor or replace sensor signals. As the number of embedded systems in products raises over time, the energy efficiency of such systems must be considered in the design. The time (processor) efficiency of the embedded software is directly related to the energy efficiency of the embedded system. Therefore, when considering some embedded software solutions, such as data-driven methods, time efficiency must be taken into account to improve energy efficiency. In this work, the energy efficiency of three data-driven methods: the Sparse Identification of Nonlinear Dynamics (SINDy), the Extreme Learning Machine (ELM), and the Random-Vector Functional Link (RVFL) network were assessed by using the creation of a real-time in-cylinder pressure sensor for diesel engines as a task. The three methods were kept with equivalent performances, whereas their relative execution time was tested and classified by their statistical rankings. Additionally, the space (memory) efficiency of the methods was assessed. The contribution of this work is to provide a guide to choose the best data-driven method to be used in an embedded system in terms of efficiency.

关键词： Support vector machines Ranking (statistics) Radio frequency Embedded systems Neurons Energy efficiency Real-time systems

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STATISTICAL ISSUES AND PROBLEMS IN GROUND-WATER DETECTION MONITORING AT HAZARDOUS-WASTE FACILITIES

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GROUND WATER MONITORING AND REMEDIATION 1988年第4期8卷 135-150页

作者： MCNICHOLS, RJ DAVIS, CB Roger J. McNichols is a professor of industrial engineering at the University of Toledo (Department of Industrial Engineering University of Toledo Toledo OH 43606). After receiving his Ph.D in industrial engineering from The Ohio State University he joined the faculty of Texas A and M University where he directed the Maintainability Engineering Graduate Program at Red River Army Depot. At UT he has served as associate dean of engineering and as chairman of the Systems engineering doctoral program. His research and consulting interests include reliability quality control manufacturing mathematical modeling and applied statistics. Charles B. Davis is an associate professor of mathematics at the University of Toledo (Department of Mathematics University of Toledo Toledo OH 43606). After receiving his M.S. in mathematics and statistics and his Ph.D. in statistics from the University of New Mexico he joined the Mathematics Department at UT where he established the graduate program in statistics. His research and consulting interests include statistical modeling statistical computation simultaneous inference and data analysis.

Ground water monitoring presents interesting statistical challenges, including controlling the risk of entering compliance monitoring, incorporating all modes of inherent variability into the statistical model on which tests are based, and taming the detection limit problem, all while maintaining demonstrable sensitivity to real contamination. Some of these challenges exceed textbook statistics considerably, even when considered alone, and good solutions are scarce. When these challenges are combined, the task of developing good statistical procedures or good regulations can be formidable. This article presents a number of realities of ground water monitoring that should be considered when developing statistical procedures. Recommendations made for addressing these realities include the following: (1) the false positive rate should be controlled on a facility-wide basis, rather than per well or per parameter as required in the proposed regulation (40 CFR §264); (2) multiple comparisons with control procedures are preferable to analysis of variance (ANOVA) for controlling the overall false positive rate; (3) retests can be made an explicit part of the statistical procedure in order to increase power and decrease sensitivity to distribution shape assumptions; (4) commonly used simple methods of handling below detection limit data with parametric tests, including Cohen's procedure as implemented in the U.S. EPA's Technical Enforcement Guidance Document (TEGD), should probably be avoided; (5) the statistical properties of practical quantitation limits for non-naturally occurring compounds should be studied carefully; and (6) so long as the facility-wide false positive rate is controlled, better sensitivity to real contamination is obtained by monitoring fewer well-chosen parameters at a smaller number of well-chosen locations. An evaluation of the proposed revised §264 regulation with respect to these realities reveals that it seems to be a definite improvement over the

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Hardware Particle Swarm Optimization with passive congregation for embedded applications

Hardware Particle Swarm Optimization with passive congregati...

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Southern Conference on programmable Logic

作者： Muñoz, Daniel M. Llanos, Carlos H. Coelho, Leandro Dos S. Ayala-Rincón, Mauricio Department of Mechanical Engineering Automation and Control Group/GRACO University of Brasilia Brasilia D.F. Brazil Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Parana Brazil Department of Computer Science and Mathematics University of Brasilia Brasilia D.F. Brazil

ISBN: (纸本)9781424488483

Achieving high performance optimization algorithms for embedded applications can be very challenging, particularly when several requirements such as high accuracy computations, short elapsed time, area cost, low power consumption and portability must be accomplished. This paper proposes a hardware implementation of the Particle Swarm Optimization algorithm with passive congregation (HPPSOpc), which was developed using several floating-point arithmetic libraries. The passive congregation is a biological behavior which allows the swarm to preserve its integrity, balancing between global and local search. The HPPSOpc architecture was implemented on a Virtex5 FPGA device and validated using two multimodal benchmark problems. Synthesis, simulation and execution time results demonstrates that the passive congregation approach is a low cost solution for solving embedded optimization problems with a high performance. © 2011 IEEE.

关键词： Digital arithmetic

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A Comparative Analysis between Particle Swarm Optimization and Mathematical programming for Optimal Location of Maintenance Facilities

A Comparative Analysis between Particle Swarm Optimization a...

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2019 IEEE PES Conference on Innovative Smart Grid Technologies, ISGT Latin America 2019

作者： Filho, Paulo M. O. Borba, Bruno S. M. C. Ferreira, Vitor H. Tavares, Rafael V. Queiroga, Eduardo Silva, João Marcos P. Uchoa, Eduardo Bergiante, Níssia C. R. Salgado Moreira, Bernardo Coelho MacHado, Pedro Henrique Universidade Federal Fluminense Electrical Engineering Department Niterói Brazil Universidade Federal Fluminense Computing Institute Niterói RJ Brazil Univeridade Federal da Paraíba Industrial Engineering Graduate Program João Pessoa PB Brazil Universidade Federal Fluminense Industrial Engineering Department Niterói RJ Brazil Energisa Distribuição Cuiabá MT Brazil Energisa Tocantins Palmas TO Brazil

ISBN: (纸本)9781538695678

This paper addresses the problem of maintenance facilities (depot) location in electric power distribution systems with a focus on strategic planning. Power interruptions can be harmful for both society and distribution companies. Determining the optimal number and sites of depot location to handle power interruptions in the long term can improve the quality of service. Through a good depot location, the distance from depots to work orders (WO) is minimized, operational costs can be minimized and customer interruption duration is reduced, which is a good indicator of the reliability of the system. The problem was solved by a Particle Swarm Optimization (PSO) algorithm and a Mixed Integer Linear programming (MILP) model. In addition to the real instance, some synthetic ones were generated to compare both approaches in large-sized scenarios. The computational results show that the two approaches are complementary strategies, being presented the scenarios where each proposal could provide better results. © 2019 IEEE.

关键词： Electric power distribution

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Accelerating the Shuffled Frog Leaping algorithm by parallel implementations in FPGAs

Accelerating the Shuffled Frog Leaping algorithm by parallel...

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2010 IEEE 5th International Conference on Bio-Inspired computing: Theories and Applications, BIC-TA 2010

作者： Muñoz, Daniel M. Llanos, Carlos H. Dos S. Coelho, Leandro Ayala-Rincón, Mauricio Department of Mechanical Engineering Automation and Control Group/GRACG University of Brasilia Brasilia D.F. Brazil Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Parana Brazil Department of Computer Science and Mathematics University of Brasilia Brasilia D.F. Brazil

ISBN: (纸本)9781424464388

Meta-heuristics are efficient techniques for solving large scale optimization problems in which traditional mathematical techniques are impractical or provide sub-optimal solutions. The Shuffled Frog Leaping algorithm (SFLA) is a stochastic iterative method, bio-inspired on the memetic evolution of a group of frogs when seeking for food, which combines the social behavior-based of the particle swarm optimization technique (PSO) and the global information exchange of memetic algorithms. However, the SFLA algorithm suffers on large execution times, being this problem clearly evident when solving complex optimization problems for embedded applications. This drawback can be overcome by exploiting the parallel capabilities of the SFLA. This paper proposes a hardware parallel implementation of the SFLA algorithm (HPSFLA) using FPGAs (Field programmable gate Arrays) and the efficient floating-point arithmetic. The proposed architecture allows the SFLA to improve the functionality of the algorithm as well as to decrease the execution times by implementing parallel frogs and parallel memeplexes. Three well-known benchmark problems have been used to validate the implemented algorithm and simulation results demonstrate that the HPSFLA speeds-up by factors of 362, 727 and 211 a C-code implementation using an embedded microprocessor for the Sphere, Rastrigin and Rosenbrock benchmarks problems, respectively. Synthesis, simulation and execution time results demonstrate the effectiveness of the proposed HPSFLA architecture for embedded optimization systems. © 2010 IEEE.

关键词： Global optimization

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COMPETITIVE ADVANTAGE MODEL THROUGH KNOWLEDGE MANAGEMENT systems IMPLEMENTATION TO OPTIMIZE BUSINESS SUSTAINABILITY 9

COMPETITIVE ADVANTAGE MODEL THROUGH KNOWLEDGE MANAGEMENT SYS...

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9th International Conference on Information Technology: IoT and Smart City, ICIT 2021

作者： Sardjono, Wahyu Lusia, Erma Utomo, Hargo Sukardi, Samudra Rahmasari, Aninda Regent Montororing, Yuri Delano Information Systems Management Department Binus Graduate Program Bina Nusantara University Indonesia Research Capacity Building Research & Development Bina Nusantara University Indonesia Department of Management Faculty of Economic and Business Gajah Mada University Indonesia Graduate Program Faculty of Economy and Business University of Indonesia Indonesia International Relations Department Faculty of Humanities Bina Nusantara University Indonesia Industrial Engineering Study Program Bhayangkara University Indonesia

ISBN: (纸本)9781450384971

Complaint resolution that arise due to internal and external factors in a company can be monitored through the Service Recovery Index (SRI), and SRI is developed through a number of factors that influence it. Meanwhile, the SRI model needs to be developed to see the business sustainability through implementation knowledge management system in the organization. The data collection method was carried out, starting with building a research instrument based on knowledge management theory and continued with observation and distributing questionnaires to respondents who were involved in the business process of managing SRI. The data analysis method was used to process the data from the questionnaire, factor analysis method was used and the method to build the model used was the regression analysis method. The results obtained from this study are the discovery of 4 (four) factors with a number of indicators that are grouped on each formed factor, which can then be made and built a readiness model that reflects current conditions, so that it can be used to build predictions in the future related to readiness. implementation of knowledge management system development in order to support increased understanding of the service recovery index in the organization. © 2021 ACM.

关键词： Knowledge management

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Considerations on loop pairing in MIMO processes. A multi-criteria analysis

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IFAC-PapersOnLine 2017年第1期50卷 4454-4459页

作者： Herrero J.M. Reynoso-Meza G. Ramos C. Blasco X. Instituto Universitario de Automática e Informática Industrial Universitat Politècnica de València Camino de Vera s/n Valencia 46022 Spain Industrial and Systems Engineering Graduate Program PPGEPS Polytechnic School Pontifical Catholic University of Paraná PUCPR Rua Imaculada Conceição 1155 Curitiba PR code 80215-901 Brazil

In this paper a new multi-objective approach for loop pairing in multi-input/multi-output processes is studied. Each controller structure of proposed input-output pairing is considered as a possible design concept. Under the meaningful objective space, defined by the control engineer, the concepts are compared and a final controller with a given trade-off is chosen. By means of an example, the paper establishes several findings: first, the controller type can be relevant when deciding on possible pairings and second, it is even more relevant the objectives chosen by the designer and his/her preferences. These findings point to multi-objective approach pairing as a powerful and promising technique. © 2017

关键词： loop pairing Multi-input/multi-output systems Multi-objective optimization Multiloop control

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In the Search for the Balance Between Real and Synthetic Images in Multi-Class Detection systems

In the Search for the Balance Between Real and Synthetic Ima...

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IEEE Conference on industrial Electronics and Applications (ICIEA)

作者： Vitória Biz Cecchetti Marcelo Rudek Roberto Z. Freire Industrial and Systems Engineering Pontifical Catholic University of Parana (PUCPR - PPGEPS) Curitiba Brazil Industrial and Systems Engineering Graduate Program (PPGEPS) Universidade Tecnoló gica Federal do Paraná (UTFPR) Curitiba Brazil

ISBN: (数字)9798350360868

ISBN: (纸本)9798350360875

Intelligent systems focused on traffic management have been in evidence in recent years, and applications related to vehicle detection and tracking, speed estimation, and traffic flow identification have become an interesting research topic. For the previously mentioned tasks, a large number of data has to be gathered to train deep learning algorithms, but collecting that data can be a time and resource-consuming task. Therefore, the use of synthetic data has become a viable option that helps to minimize data acquisition problems, but when misused, it can negatively impact the model's quality. This paper presents a systematic literature review based on the use of synthetic images to train object detection models in urban scenarios, aiming at identifying the ideal ratio between real and synthetic images that can benefit those models and the best methods to produce synthetic images. This study identified that there is no consensus on the number of synthetic images that can help to generate a more accurate model, due to the low number of papers addressing this relationship, however, it was noted that the use of generative adversarial networks (GANs) can create synthetic images that are more similar to real images, bringing benefits for training detection models, although without identifying how the use of images generated by this method can help in the relationship between synthetic and real.

关键词： Training Analytical models Accuracy Vehicle detection Object detection Generative adversarial networks Data models

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