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检索条件"主题词=adaptive genetic algorithm"

共 444 条记录，以下是11-20 订阅

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adaptive genetic algorithm Applied in Coordinated Control of PSS and STATCOM

Adaptive Genetic Algorithm Applied in Coordinated Control of...

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International Conference on Measuring Technology and Mechatronics Automation

作者： Liu Zhijian Yu Jilai Shu Hongchun Harbin Inst Technol Dept Elect Engn Harbin 150006 Peoples R China Kunming Univ Sci & Technol Fac Power Engn Kunming Peoples R China

ISBN: (纸本)9780769535838

Firstly, an adaptive genetic algorithm (AGA) is proposed. For traditional genetic algorithm, it easily premature and falls into local optima. A better initial population should have differences among the individuals and distributes uniformly in the whole solution space. In AGA of this paper, initial population is selected according to the Hamming distances to solve this question. adaptive crossing and mutation probability method also is presented to optimize the population and find the global solution. Secondly, a multi-aim optimal designing method which is based on AGA is applied in the cooperation control of power system stabilizer (PSS) and static compensator (STATCOM). Simulation results show that, used the solution presented in the paper, the stability of power angle and voltage can be effectively enhanced.

关键词： adaptive genetic algorithm Power system stability PSS STATCOM

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adaptive genetic algorithm for Improving Prediction Accuracy of a Multi-criteria Recommender System 12

Adaptive Genetic Algorithm for Improving Prediction Accuracy...

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IEEE 12th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC)

作者： Hamada, Mohamed Abdulsalam, Latifat Ometere Hassan, Mohammed Univ Aizu Software Engn Lab Aizu Wakamatsu Fukushima Japan African Univ Sci & Technol Dept Comp Sci & Engn Abuja Nigeria Bayero Univ Kano Dept Software Engn Kano Nigeria

ISBN: (纸本)9781538666890

Recommender systems are software tools used to make valuable recommendations to users. Traditionally, recommender systems use information obtained from ratings of an item by users with similar opinions to make recommendations. A user uses a single rating to represent the degree of likeness of an item in traditional recommender systems. Though this approach has reasonably shown a good prediction accuracy, however, the performance of traditional recommender systems is considered inadequate, as users could have different opinions based on some specific features of an item. Multi-criteria recommendation extends the traditional techniques by incorporating ratings for various attributes of the items. It provides better recommendations for users as the system allows the opportunity for users to specify their preferences based on different attributes of user item, which improves prediction accuracy. In this paper, we proposed an aggregation function based method that uses an adaptive genetic algorithm to efficiently incorporate the criteria ratings for improving the accuracy of the multi-criteria recommender system. We carried out an experiment using a dataset for multi-criteria recommendations of movies to users. The experimental result shows that our proposed approach provides better accuracy than the corresponding traditional technique.

关键词： Recommender system adaptive genetic algorithm Multi-criteria recommender system Asymmetric singular value decomposition Prediction accuracy

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adaptive genetic algorithm to Select Training Data for Support Vector Machines 17

引用

17th European Conference on Applications of Evolutionary Computation (EvpApplications)

作者： Nalepa, Jakub Kawulok, Michal Silesian Tech Univ Gliwice Poland

ISBN: (纸本)9783662455234;9783662455227

This paper presents a new adaptive genetic algorithm (AGA) to select training data for support vector machines (SVMs). SVM training data selection strongly influences the classification accuracy and time, especially in the case of large and noisy data sets. In the proposed AGA, a population of solutions evolves with time. The AGA parameters, including the chromosome length, are adapted according to the current state of exploring the solution space. We propose a new multi-parent crossover operator for an efficient search. A new metric of distance between individuals is introduced and applied in the AGA. It is based on the fast analysis of the vectors distribution in the feature space obtained using principal component analysis. An extensive experimental study performed on the well-known benchmark sets along with the real-world and artificial data sets, confirms that the AGA outperforms a standard GA in terms of the convergence capabilities. Also, it reduces the number of support vectors and allows for faster SVM classification.

关键词： adaptive genetic algorithm Support vector machines Training data selection

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adaptive genetic algorithm Based on Crossover and Mutation Method for Optimization of Poultry Feed Composition 3

Adaptive Genetic Algorithm Based on Crossover and Mutation M...

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3rd International Conference on Sustainable Information Engineering and Technology (SIET)

作者： Rikatsih, Nindynar Mahmudy, Wayan Firdaus Brawijaya Univ Fac Comp Sci Malang Indonesia

ISBN: (纸本)9781538674079

The problem that often comes in poultry industry is the process of composition selection of poultry feed that is not efficient. Feed ingredients with high nutrients have a relatively expensive price while low-cost feeds contain inadequate nutritional needs of livestock. Breeders should reduce the cost of spending to generate higher income. These problems can be solved using genetic algorithms to obtain the composition of feed ingredients in accordance with the needs of livestock nutrition and have a minimum price. The simple genetic algorithm applied takes a long time to reach the optimal solution. Therefore, genetic operator should be improved to increase the ability of genetic algorithm in finding the optimal solution. This study uses a combination of different crossover and mutation methods. We propose extended intermediate and one cut point method in the crossover process. We use two method of mutation which are random and inverse mutation. The experiment result shows that the optimum population size is 250, the best combination of cr and mr of this experiment is 0.7 and 0.3 and the number of generations is 1000. According to the result, the experiment proves that adaptive genetic algorithm is efficient in solving this kind of problems.

关键词： genetic algorithm adaptive genetic algorithm optimization poultry feed

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adaptive genetic algorithm for Multiple QoS Anycast Routing

Adaptive Genetic Algorithm for Multiple QoS Anycast Routing

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IEEE International Conference on Intelligent Computing and Intelligent Systems

作者： Li Taoshen Ge Zhihui Guangxi Univ Sch Comp Elect & Informat Nanning 530004 Peoples R China Guangxi Univ Sch Comp Elect & Informat Nanning 530004 Peoples R China

ISBN: (纸本)9781424447541

As a new network addressing and routing scheme, anycast has been defined as a standard communication model in IPv6 The multiple QoS constrained anycast routing problem is a nonlinear combination optimization problem, which is proved to be a NP complete problem This paper studies anycast routing technology with multiple QoS constraints and proposes a multiple QoS anycast routing algorithm based adaptive genetic algorithm This algorithm uses adaptive probabilities of crossover and mutation over and over again in simple genetic algorithm Fitness scaling can guarantee the diversity of populations, which is beneficial to find global optimal solution Simulation results show the efficiency of our algorithm It can satisfy the constrained condition of multiple QoS, balance network load fairly, and improve the quality of network service

关键词： anycast Quality of Service(QoS) routing algorithm adaptive genetic algorithm load balance

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adaptive genetic algorithm for Reducing Average Waiting Time for Road Traffic Signals 5

Adaptive Genetic Algorithm for Reducing Average Waiting Time...

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5th International Conference on Innovative Trends in Information Technology (ICITIIT)

作者： Sankaranarayanan, Manipriya Yerramsetty, Sudhasree Kakkera, Santosh Kumar, Nitant Indian Inst Informat Technol Sri City Dept Comp Sci & Engn Chittoor Andhra Pradesh India

ISBN: (纸本)9798350386813;9798350386820

Addressing the important need to reduce average waiting times at road traffic signals is crucial, this research offers an optimal strategy targeted at improving the traffic flow efficiency. However, despite its success in lowering wait times, the suggested system has difficulties in dealing with unanticipated traffic spikes. The work proposes an adaptive genetic algorithm (AGA) to reduce traffic waiting time and incorporates complex algorithms and modules along with heuristic algorithms and various sorts of crossovers to achieve notable outcomes to minimize traffic congestion. The performance of AGA was evaluated using the Simulation for Urban MObility (SUMO). The simulation included a four-way junction in which a network with default traffic signal information was simulated and their modified phase time using AGA in network waiting time was also simulated and analysed. The analysis revealed improved results in optimization, with considerable gains produced by combining either of the crossover approaches that have been utilized.

关键词： Traffic Optimization Traffic Light Control SUMO software genetic algorithm adaptive genetic algorithm Waiting Time

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adaptive genetic algorithm Based Multi-Objective Optimization for Photovoltaic Cell Design Parameter Extraction 1

Adaptive Genetic Algorithm Based Multi-Objective Optimizatio...

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1st International Conference on Power Engineering Computing and CONtrol (PECCON)

作者： Kumari, Ashwini P. Geethanjali, P. VIT Univ Sch Elect Engn Vellore Tamil Nadu India REVA Univ Bangalore 560064 Karnataka India

In this paper, an enhanced evolutionary computing algorithm has been attempted for photo voltaic (PV) design parameter extraction using adaptive genetic algorithm. The I-V curve fitting approach has been used to find optimal photovoltaic parameters Unlike single objective function based approaches, multiple objective functions including, least mean square error and Pearson residual error optimization are considered to fit the I-V curve. A cumulative fitness function is derived using both objectives that alleviate computational complexity, local minima and convergence. Importantly, Pearson residual error optimization (PRO) optimizes least mean square error (LSE) reduction while alleviating the probability of under/over-fitting that ensures optimal PV design parameter identification (C) 2017 The Authors. Published by Elsevier Ltd.

关键词： PV Design Parameter Extraction adaptive genetic algorithm Multi-Objective Optimization I-V Curve Fitting

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adaptive genetic algorithm Evidence Model and Its Application for Discriminating Enemy Radar Operation Intention

Adaptive Genetic Algorithm Evidence Model and Its Applicatio...

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24th Chinese Control and Decision Conference (CCDC)

作者： Pan Wei Li Wenjun Yang Jinsong Shenyang Artillery Acad Elect Detect Dept Shenyang 110867 Peoples R China Shenyang Artillery Acad Self Propelled Artillery & Command Shenyang 110867 Peoples R China

ISBN: (纸本)9781457720727

Considering the signatures captured from information about the hostile radar operation intention, this paper puts forward concepts of the simplest evidence support format, duality evidence support format, and same-type evidence and so on. Based on these concepts, it discusses the problem of the orthogonal sum with the duality evidence support format expressed as the simplest evidence support format, and then, drawing its conclusion to show the relation between the enemy intention and the characteristic information. Thereby, it establishes a system for radar operation intention discrimination to complete the final determinant. This new model brings expression and combination of evidences simplified and computation reduced. By practical application, this algorithm has been proved feasibility and effectiveness.

关键词： radar intention recognition evidence model performance analysis combination algorithm adaptive genetic algorithm

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adaptive genetic algorithm to Optimize the Parameters of Evaluation Function of Dots-and-Boxes 1

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12th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness (QShine)

作者： Bi, Fangming Wang, Yunchen Chen, Wei China Univ Min & Technol Sch Comp Sci & Technol Xuzhou 221116 Jiangsu Peoples R China

ISBN: (数字)9783319607177

ISBN: (纸本)9783319607177;9783319607160

Designed an evaluation function with parameters, and used genetic algorithm to optimize the parameters. This paper considers the objective function's variation trends in searching point and the information is added to the fitness function to guide the searching. Simultaneously adaptive genetic algorithm enables crossover probability and mutation probability automatically resized according to the individual's fitness. These measures have greatly improved the convergence rate of the algorithm. Sparring algorithm is introduced to guide the training, using gradient training programs to save training time. Experiments show skills in playing Dots-and-Boxes are greatly improved after its evaluation function parameters are optimized.

关键词： adaptive genetic algorithm Evaluation function Game

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adaptive genetic algorithm Based Data Classification Rules Learning System

Adaptive Genetic Algorithm Based Data Classification Rules L...

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International Conference on Advanced Materials and Information Technology Processing (AMITP 2011)

作者： Shi, Haibin Li, Yi China Univ Min & Technol Sch Comp Sci & Technol Xuzhou Jiangsu Peoples R China

ISBN: (纸本)9783037851579

It's a worthy research topic to use genetic algorithm for classification rules in data mining. In this paper, it was studied and researched in-depth. Firstly, we combined genetic algorithm and machine learning together, and then analyzed architecture of the genetic algorithm-based classification system, and also its development concrete structure was given. Secondly, we proposed a data classification rules learning system based on adaptive genetic algorithm, which can learn the classification rules accurately from the dataset. Finally the standard Play Tennis dataset was used for a closed test and after learning the system got three classification rules all with 100% accuracy rate, which fully demonstrated the feasibility of this algorithm.

关键词： Data Classification genetic algorithm adaptive genetic algorithm Classification System Classification Rule

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