检索结果-内蒙古大学图书馆

A modified cultural algorithm with a balanced performance for the differential evolution frameworks

KNOWLEDGE-BASED SYSTEMS 2016年 111卷 73-86页

作者： Ali, Mostafa Z. Awad, Noor H. Suganthan, Ponnuthurai N. Reynolds, Robert G. Jordan Univ Sci & Technol Sch Comp & Informat Irbid 22110 Jordan Princess Sumaya Univ Technol King Hussein Fac Comp Sci Amman 11941 Jordan Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore Wayne State Univ Coll Engn Detroit MI 48202 USA

Numerous different methodologies have been introduced in the last few decades to provide efficient solutions for complex real-world problems and other optimization problems. This work focuses on the development of a simple hybrid cultural learning theme with a balanced performance for differential evolution frameworks. It is intended to be always efficient for a diverse set of optimization tasks. As different optimization algorithms behave differently depending on the problems, the combination of the best behaviors from different search strategies seems desirable. The proposed work explores the combination of the explorative/exploitative strengths of two heuristic search techniques, which discretely provide competitive results. Differential evolution is used as the population space for cultural algorithm, and is used to guide knowledge dissemination from the knowledge sources in the belief space. Here, a new influence function is introduced that adjusts the membership of each of the knowledge sources. The algorithm has been tested with the conditions and benchmark problems defined for the IEEE CEC2013 special session and competition on real-parameter single objective optimization. The paper also investigates the application of the new algorithm to a set of real-life problems concerning optimizing the weight a tension/compression spring and minimizing the fabrication cost of a welded beam engineering problem. The proposed algorithm appears to have a significant impact on the algorithmic functioning as it reliably augments the performance of the differential evolution frameworks with which it is integrated. Benchmark results for most of the synthetic functions from the special session show that the balanced hybrid obtains superior performance compared to the other competent algorithms. It scales well with the increasing dimensionality and converges in the close proximity of the global optimum for complex functions. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Evolutionary algorithm cultural algorithm Differential evolution Optimization Hybrid algorithm

来源：评论

学校读者我要写书评

暂无评论

An improved multiobjective cultural algorithm with a multistrategy knowledge base

引用

APPLIED INTELLIGENCE 2022年第2期52卷 1157-1187页

作者： Mao, Zhengyan Liu, Mandan East China Univ Sci & Technol Key Lab Adv Control & Optimizat Chem Proc Minist Educ Shanghai 200237 Peoples R China

Based on the dual-inheritance framework of cultural evolution, an improved multiobjective cultural algorithm (IMOCA) with a multistrategy knowledge base is presented in this paper. Inspired by the original versions of the cultural algorithm (CA), four basic types of knowledge sources, i.e., normative, situational, topographical and historical knowledge, are effectively utilized in the proposed IMOCA. Several modifications with the knowledge base of the IMOCA are made to tackle the characteristics of the multiobjective problem. Situational knowledge is used as an external repository for storing elite individuals, and the redesigned topographical knowledge functions as a search engine to broaden the expansion of the obtained solution set. The historical knowledge used in the IMOCA aims to select a productive knowledge source to generate new individuals. Furthermore, a simple mutation scheme is introduced into the knowledge base as an influence function for the purpose of fine tuning in the late stage of search. After configuring the parameters used in IMOCA, two classic benchmark suites, i.e., WFG and MaF, are used to assess the performance of the IMOCA in approaching the Pareto fronts (PFs) with accuracy and diversity. Nondominated solution sets obtained by the IMOCA are compared with 8 state-of-the-art multiobjective algorithms available in the literature. A statistical analysis is conducted, which reveals that, by modifying the basic knowledge structure of the CA, the proposed multiobjective cultural algorithm is competent enough to handle multiobjective problems with competitive performance.

关键词： Multiobjective optimization Evolutionary algorithm cultural algorithm Dual-inheritance framework Knowledge-based evolutionary computation Nondominated sorting

来源：评论

学校读者我要写书评

暂无评论

Application of cultural algorithm to generation scheduling of hydrothermal systems

引用

ENERGY CONVERSION AND MANAGEMENT 2006年第15-16期47卷 2192-2201页

作者： Yuan, Xiaohui Yuan, Yanbin Huazhong Univ Sci & Technol Dept Hydropower Engn Wuhan 430074 Hubei Peoples R China Wuhan Univ Technol Dept Environm Engn Wuhan 430071 Peoples R China

The daily generation scheduling of hydrothermal power systems plays an important role in the operation of electric power systems for economics and security, which is a large scale dynamic non-linear constrained optimization problem. It is difficult to solve using traditional optimization methods. This paper proposes a new cultural algorithm to solve the optimal daily generation scheduling of hydrothermal power systems. The approach takes the water transport delay time between connected reservoirs into consideration and can conveniently deal with the complicated hydraulic coupling simultaneously. An example is used to verify the correctness and effectiveness of the proposed cultural algorithm, comparing with both the Lagrange method and the genetic algorithm method. The simulation results demonstrate that the proposed algorithm has rapid convergence speed and higher solution precision. Thus, an effective method is provided to solve the optimal daily generation scheduling of hydrothermal systems. (c) 2005 Elsevier Ltd. All rights reserved.

关键词： cultural algorithm hydrothermal systems daily generation scheduling

来源：评论

学校读者我要写书评

暂无评论

A cultural algorithm for Optimal Design of Truss Structures

引用

LATIN AMERICAN JOURNAL OF SOLIDS AND STRUCTURES 2015年第9期12卷 1721-1747页

作者： Jalili, Shahin Hosseinzadeh, Yousef Islamic Azad Univ Urmia Branch Young Researchers & Elite Club Orumiyeh Iran Univ Tabriz Fac Civil Engn Tabriz Iran

A cultural algorithm was utilized in this study to solve optimal design of truss structures problem achieving minimum weight objective under stress and deflection constraints. The algorithm is inspired by principles of human social evolution. It simulates the social interaction between the peoples and their beliefs in a belief space. cultural algorithm (CA) utilizes the belief space and population space which affects each other based on acceptance and influence functions. The belief space of CA consists of different knowledge components. In this paper, only situational and normative knowledge components are used within the belief space. The performance of the method is demonstrated through four benchmark design examples. Comparison of the obtained results with those of some previous studies demonstrates the efficiency of this algorithm.

关键词： cultural algorithm Truss structure design Size optimization

来源：评论

学校读者我要写书评

暂无评论

An improved cultural algorithm and its application in image matching

引用

MULTIMEDIA TOOLS AND APPLICATIONS 2017年第13期76卷 14951-14968页

作者： Yan, Xuesong Song, Tao Wu, Qinghua China Univ Geosci Sch Comp Sci Wuhan 430074 Hubei Peoples R China China Univ Geosci Ctr Network & Educ Technol Wuhan 430074 Hubei Peoples R China WuHan Inst Technol Fac Comp Sci & Engn Wuhan 430074 Hubei Peoples R China

cultural algorithm (CA) are a class of computational models derived from observing the cultural evolution process in nature and is used to solve complex calculations of the new global optimization search algorithms. Aiming at the traditional cultural algorithm has poor precision and trap into local optimum of global optimization. In this paper, introduce the isolation niche technology into the traditional cultural algorithm. With improvements, the algorithm is less likely to trap in local optimum. According to the test of one set of benchmark function, the proposed algorithm has greater improvements than ordinal cultural algorithm in the aspects of convergence precision and stability. In this paper, introduce the proposed algorithm into the image matching problem, and the simulation test shows that the algorithm for image matching problem has made great effects in stability and convergence precision.

关键词： cultural algorithm Isolation niche technology Population Image matching

来源：评论

学校读者我要写书评

暂无评论

A Hybrid of Differential Evolution and cultural algorithm for Recurrent Functional Neural Fuzzy Networks and Its Applications

引用

INTERNATIONAL JOURNAL OF FUZZY SYSTEMS 2012年第4期14卷 519-529页

作者： Lin, Hsueh-Yi Lin, Cheng-Jian Wu, Chi-Feng Chen, Cheng-Hung Natl Chin Yi Univ Technol Comp Sci & Informat Engn Dept Taichung 411 Taiwan Wenzao Ursuline Coll Languages Digital Content Applicat & Management Dept Kaohsiung 811 Taiwan Natl Formosa Univ Dept Elect Engn Yunlin 632 Taiwan

By applying the recurrent functional neural fuzzy network (RFNFN) and a novel evolutionary learning algorithm this study presents an evolutionary neural fuzzy network (NFN). The proposed new evolutionary learning algorithm is based on an effective combination of the modified differential evolution (MDE) and cultural algorithm, which is called the cultural-based MDE (CMDE) method. After the four individuals are randomly chosen from the population for mutation, the proposed CMDE method can search the whole solution space more efficiently. In addition, during the evolutionary process of the cultural algorithm, the performance enhancement is highly affected by the belief space extraction and use of the corresponding information. The proposed RFNFN model uses functional-link neural networks (FLNN) as the consequent part of the fuzzy rules, while in this study the orthogonal polynomials and linearly independent functions are adapted as in a functional expansion of the FLNNs. In summary, the RFNFN model is not only able to generate the consequent part as a nonlinear combination of input variables, but also capable of tackling complicated temporal problem through the added feedback connections. Experimental results in prediction and control applications have shown that the proposed RFNFN-CMDE mechanism outperforms other compared approaches, in terms of convergent speed and root-mean-squared error.

关键词： cultural algorithm differential evolution functional link neural network neural fuzzy networks control prediction

来源：评论

学校读者我要写书评

暂无评论

Enhanced cultural algorithm to solve multi-objective attribute reduction based on rough set theory

引用

MATHEMATICS AND COMPUTERS IN SIMULATION 2020年 170卷 332-350页

作者： Abdolrazzagh-Nezhad, Majid Bozorgmehr Univ Qaenat Fac Engn Dept Comp Engn Qaen Iran

In extracting hidden information from a data, its high dimension can create challenges in the quality of the extracted information and the search space size. Attribute reduction based on minimizing both missed information and selected subset attributes is logical solution for the challenge. Rough set theory (RST) is an information recognition technique in uncertain data that it shows the value missed information for the selected attributes. In this paper, a multi-objective attribute reduction (MOAR) is modeled by designing a new effective cost function to optimize the minimum number of attributes with the maximum dependency coefficient of the RST. Due to the MOAR is an NP-hard problem, an enhanced draft of cultural algorithm, as a continuous optimization algorithm, is proposed to solve it, as a discrete problem for the first time. The cultural algorithm (CA) with a dual inheritance system is enhanced by utilizing just normative and situational components to generate new individuals and planning a novel heuristic to discrete population and belief spaces. With regard to design the research problem, the CA and five algorithms are implemented to compare their results on twelve well-known UCI datasets in three categories sizes;small, middle and large. The tuning algorithm's parameters to find the best possible values are done and different size of the population is considered to evaluate the sensitivity of the algorithms on the population size parameter. The experimental results show that the proposed algorithm is able to find competitive results when compared to the state-of-the-art algorithms. (C) 2019 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.Y. All rights reserved.

关键词： Multi-objective attribute reduction Rough set theory cultural algorithm Discretization Population sensitivity

来源：评论

学校读者我要写书评

暂无评论

Economic environmental dispatch using an enhanced multi-objective cultural algorithm

引用

ELECTRIC POWER SYSTEMS RESEARCH 2013年 99卷 18-29页

作者： Zhang, Rui Zhou, Jianzhong Mo, Li Ouyang, Shuo Liao, Xiang Huazhong Univ Sci & Technol Sch Hydropower & Informat Engn Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Hubei Key Lab Digital Valley Sci & Technol Wuhan 430074 Peoples R China

Economic environment dispatch (EED) is a significant optimization problem in conventional fossil fuel fired power system to distribute load demand reasonably and scientifically so that fuel cost and emission issues are optimized simultaneously while satisfying various constraints. Valve-point effect, prohibited operation zones (POZs) and transmission losses make the LED a non-smooth and non-convex optimization problem. In order to solve this constrained multi-objective optimization problem including competing objectives as well as complex constraints, an enhanced multi-objective cultural algorithm (EMOCA) is proposed in this paper. The proposed method combines cultural algorithm framework with particle swarm optimization (PSO) to carry though the evolution of population space. Besides, two knowledge structures of belief space in CA are redefined according to the features of EED problem. Moreover, an effective constrain handling method is proposed to handle the equality and inequality constraints of LED problem. Simulation results of test systems demonstrate the capability of the proposed algorithm to generate well-distributed Pareto optimal solutions in a single run. Compared with some current methods, EMOCA has a good performance in finding a diverse set of solutions and in converging near the true Pareto optimal front with lower fuel cost and emission issues synthetically. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Economic environmental dispatch Prohibited operation zones (POZs) Multi-objective optimization cultural algorithm Constraint handle

来源：评论

学校读者我要写书评

暂无评论

Artificial immune network clustering based on a cultural algorithm

引用

EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING 2020年第1期2020卷 1-17页

作者： Deng, Liyuan Yang, Ping Liu, Weidong Xian Res Inst High Technol Xian Peoples R China

Data mining technology has been applied in many fields. Prototype-based cluster analysis is an important data mining method, but its ability to discover knowledge is limited because of the need to know the number of target data categories and cluster prototypes in advance. Artificial immune evolutionary network clustering is a clustering method based on network structure. Compared with prototype-based cluster analysis, it has the advantage of realizing unsupervised learning and clustering without any prior knowledge of data. However, artificial immune evolutionary network clustering also has problems such as a lack of guidance in the clustering process, fuzzy boundary sensitivity, and difficulty in determining parameters. To solve these problems, an artificial immune network clustering algorithm based on a cultural algorithm is proposed. First, three kinds of knowledge are constructed: normative knowledge is used to regulate the spatial range of population initialization to avoid blindness;state knowledge is used to distinguish the type of antigen, and immune defense measures are taken to prevent the network structure caused by noise and boundaries from being unclear;and topology knowledge is used to guide the antigen for optimal antibody search. Second, topology knowledge in the cultural algorithm is used to characterize the distribution of antigens and antibodies in space, and elite learning is used to improve the traditional clone mutation operator. Based on the shadow set theory, a method for adaptively determining the compression threshold is proposed. Finally, the results of simulation experiments show that the proposed algorithm can effectively overcome the above problems, and the clustering performances on a synthetic dataset and an actual dataset are satisfactory.

关键词： Clustering Immune network cultural algorithm Immune defense Shadow set theory

来源：评论

学校读者我要写书评

暂无评论

Efficient DE-based symbiotic cultural algorithm for neuro-fuzzy system design

引用

APPLIED SOFT COMPUTING 2015年 34卷 18-25页

作者： Chen, Cheng-Hung Yang, Sheng-Yen Natl Formosa Univ Dept Elect Engn Huwei Township 632 Yunlin County Taiwan

This study proposes a differential-evolution-based symbiotic cultural algorithm (DESCA) for the implementation of neuro-fuzzy systems (NFS) to solve nonlinear control system problems. DESCA adopts symbiotic evolution to decompose a fuzzy system into multiple fuzzy rules as multiple subpopulations. In addition, DESCA randomly selects fuzzy rules from different subpopulations that combine into a complete solution whose performance is be evaluated. Moreover, DESCA uses various mutation strategies of differential evolution as five knowledge sources in the belief space. These knowledge sources influence the population space in the cultural algorithm and can be used as models to guide the feasible search space. Finally, the proposed algorithm is applied to various simulations. The results demonstrate the effectiveness of this approach. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Differential evolution Symbiotic evolution cultural algorithm Neuro-fuzzy systems Nonlinear control system

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：