检索结果-内蒙古大学图书馆

8th International Conference on Soft Computing for Problem Solving (SocProS)

作者： Chaudhary, Reshu Banati, Hema Univ Delhi Dept Comp Sci Delhi 110007 India Dyal Singh Coll Lodhi Rd Delhi 110003 India

ISBN: (纸本)9789811500350;9789811500343

Modified shuffled multi-population bat algorithm (MSMPbat) is a recently proposed swarm algorithm. It divides its population into multiple subpopulations (SPs), each of which uses different parameter settings and evolves independently using an enhanced search mechanism. For information exchange among these SPs, a solution from one SP is copied to the next after every generation. This process leads to duplication of solutions over time. To overcome this drawback, different techniques are introduced. Opposition-based learning is used to generate a diverse starting population. For information exchange, if a solution comes too close to the swarm best, only then it is sent (moved, not copied) to another swarm. Four techniques are proposed to select this second swarm. Initially, the selection probability of each technique is same. The algorithm adaptively updates these probabilities based on their success rate. The swarm which gave up the solution uses a modified opposition-based learning technique to generate a new solution. These changes help to maintain the overall diversity of the population. The proposed approach, namely, adaptive multi-swarm bat algorithm (AMBA), is compared to six algorithms over 20 benchmark functions. Results establish the superiority of adaptive multi-swarm bat algorithm.

关键词： bat algorithm Multi-swarm optimization Adaptive algorithm Numerical optimization

来源：评论

学校读者我要写书评

暂无评论

Modified OFS-RDS bat algorithm for IFS encoding of bitmap fractal binary images

引用

ADVANCED ENGINEERING INFORMATICS 2021年 47卷 101222-101222页

作者： Galvez, Akemi Iglesias, Andres Diaz, Jose A. Fister, Iztok Lopez, Joaquin Fister, Iztok, Jr. Toho Univ Fac Sci Dept Informat Sci 2-2-1 Miyama Funabashi Chiba 2748510 Japan Univ Cantabria Dept Appl Math & Computat Sci ETSI Caminos Canales & Puertos Avda Castros S-N Santander 39005 Spain Univ Cantabria Sch Civil Engn Avda Castros 44 E-39005 Santander Spain Univ Maribor Fac Elect Engn & Comp Sci SI-2000 Maribor Slovenia Univ Cantabria Sch Civil Engn R&D EgiCAD Avda Castros 44 Santander 39005 Spain

This work is an extension of a previous paper (presented at the Cyberworlds 2019 conference) introducing a new method for fractal compression of bitmap binary images. That work is now extended and enhanced through three new valuable features: (1) the bat algorithm is replaced by an improved version based on optimal forage strategy (OFS) and random disturbance strategy (RDS);(2) the inclusion of new similarity metrics;and (3) the consideration of a variable number of contractive maps, whose value can change dynamically over the population and over the iterations. The first feature improves the search capability of the method, the second one improves the reconstruction accuracy, and the third one computes the optimal number of contractive maps automatically. This new scheme is applied to a benchmark of two binary fractal images exhibiting a complex and irregular fractal shape. The graphical and numerical results show that the method performs very well, being able to reconstruct the input images with high accuracy. It also computes the optimal number of contractive maps in a fully automatic way. A comparative work with other alternative methods described in the literature is also carried out. It shows that the presented method outperforms the previous approaches significantly.

关键词： Swarm intelligence bat algorithm Fractal compression Iterated function systems Bitmap images

来源：评论

学校读者我要写书评

暂无评论

COEBA: A Coevolutionary bat algorithm for Discrete Evolutionary Multitasking 20th

COEBA: A Coevolutionary Bat Algorithm for Discrete Evolution...

引用

20th Annual International Conference on Computational Science (ICCS)

作者： Osaba, Eneko Del Ser, Javier Yang, Xin-She IgIesias, Andres Galvez, Akemi Basque Res & Technol Alliance BRTA TECNALIA Derio 48160 Spain Univ Basque Country UPV EHU Bilbao 48013 Spain Middlesex Univ London London NW4 4BT England Univ Cantabria Santander 39005 Spain Toho Univ Funabashi Chiba Japan

ISBN: (纸本)9783030867973;9783030504250

Multitasking optimization is an emerging research field which has attracted lot of attention in the scientific community. The main purpose of this paradigm is how to solve multiple optimization problems or tasks simultaneously by conducting a single search process. The main catalyst for reaching this objective is to exploit possible synergies and complementarities among the tasks to be optimized, helping each other by virtue of the transfer of knowledge among them (thereby being referred to as Transfer Optimization). In this context, Evolutionary Multitasking addresses Transfer Optimization problems by resorting to concepts from Evolutionary Computation for simultaneous solving the tasks at hand. This work contributes to this trend by proposing a novel algorithmic scheme for dealing with multitasking environments. The proposed approach, coined as Coevolutionary bat algorithm, finds its inspiration in concepts from both co-evolutionary strategies and the metaheuristic bat algorithm. We compare the performance of our proposed method with that of its Multifactorial Evolutionary algorithm counterpart over 15 different multitasking setups, composed by eight reference instances of the discrete Traveling Salesman Problem. The experimentation and results stemming therefrom support the main hypothesis of this study: the proposed Coevolutionary bat algorithm is a promising meta-heuristic for solving Evolutionary Multitasking scenarios.

关键词： Transfer Optimization Evolutionary Multitasking bat algorithm Multifactorial Optimization Traveling Salesman Problem

来源：评论

学校读者我要写书评

暂无评论

Optimized Two Dimensional Wavelet Filter from bat algorithm 7

Optimized Two Dimensional Wavelet Filter from BAT Algorithm

引用

7th IEEE International Conference on Smart Structures and Systems (ICSSS)

作者： Ravi, Renjith, V Subramaniam, Kamalraj MEA Engn Coll Elect & Commun Engn Malappuram Kerala India Karpagam Acad Higher Educ Fac Engn Elect & Commun Engn Coimbatore Tamil Nadu India

ISBN: (纸本)9781728172231

Due to the effect of a quantization error, it is not possible to fully restore the original image in the lossy wavelet-based image compression. However, the quantization error can be minimized by optimizing or evolving the filter bank. In this work, the coefficients of the standard wavelet filter and its inverse filter were optimized by evolution of bat algorithm. The optimized wavelet filters were used with the SPIHT encoder/decoder for image compression. The performance of the optimized filters in reconstruction during the decompression process was investigated using the metrics PSNR, MSE and SSIM. The results obtained show that the proposed filter outperforms standard wavelet filters by minimizing the error between the original and the decompressed image.

关键词： Optimized Wavelet Filter Evolved Wavelet Filter DWT Optimization Adaptive DWT bat algorithm Swarm Intelligence algorithm

来源：评论

学校读者我要写书评

暂无评论

Enhanced bat algorithm for Solving Non-Convex Economic Dispatch Problem 4th

Enhanced Bat Algorithm for Solving Non-Convex Economic Dispa...

引用

4th International Conference on Soft Computing and Data Mining (SCDM)

作者： Hussain, Kashif Zhu, William Salleh, Mohd Najib Mohd Ali, Haseeb Talpur, Noreen Naseem, Rashid Ahmad, Arshad Ullah, Ayaz Univ Elect Sci & Technol China Inst Fundamental & Frontier Sci Chengdu Sichuan Peoples R China Univ Tun Hussein Onn Malaysia Fac Comp Sci & Informat Technol Batu Pahat Malaysia Univ Teknol Petronas Fac Sci & Informat Technol Seri Iskandar Perak Malaysia City Univ Sci & Informat Technol Dept Comp Sci Peshawar Pakistan Univ Swabi Dept Comp Sci Swabi Pakistan

ISBN: (纸本)9783030360566;9783030360559

bat algorithm lags behind other modern metaheuristic algorithms in terms of search efficiency, due to premature convergence. Once trapped in any sub-optimal region, the algorithm is unable to escape because of deficiency in population diversity. To address this, an enhanced bat algorithm (EBA) is introduced in this paper. The EBA algorithm comes with adaptive exploration and exploitation capability, as well as, additional population diversity. This enables EBA improve its convergence ability to find even better solutions towards the end of search process, where standard BA is often trapped. To illustrate effectiveness of the proposed method, EBA is applied on non-linear, non-convex economic dispatch problem with a power generation system comprising of twenty thermal units. The experimental results suggest that EBA not only saved power generation cost but also reduced transmission losses, more efficiently as compared to original BA and other methods reported in literature. The EBA algorithm also showed enhanced convergence ability than BA towards the end of iterations.

关键词： bat algorithm Economic dispatch Power generation dispatch Optimization Non-convex

来源：评论

学校读者我要写书评

暂无评论

bat algorithm with principal component analysis

引用

INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS 2019年第3期10卷 603-622页

作者： Cui, Zhihua Li, Feixiang Zhang, Wensheng Taiyuan Univ Sci & Technol Taiyuan 030024 Shanxi Peoples R China Chinese Acad Sci Inst Automat Res Ctr Precis Sensing & Control Beijing Peoples R China

The bat algorithm (BA) is a novel evolutionary optimization algorithm, most studies of which have been performed with low-dimensional problems. To test and improve the global search ability of BA with large-scale problems, two new variants using principal component analysis (PCA_BA and PCA_LBA) are designed in this paper. A correlation threshold and generation threshold are determined using the golden section method to enhance the effectiveness of this new strategy. To test performance, CEC'2008 large-scale benchmark functions are utilized and compared with other algorithms;simulation results indicate the validity of this modification.

关键词： bat algorithm Principal component analysis Golden section method

来源：评论

学校读者我要写书评

暂无评论

Multi-label Feature Selection Method via Maximizing Correlation-based Criterion with Mutation Binary bat algorithm

Multi-label Feature Selection Method via Maximizing Correlat...

引用

International Joint Conference on Neural Networks (IJCNN) held as part of the IEEE World Congress on Computational Intelligence (IEEE WCCI)

作者： Tao, Yuanyuan Li, Jun Xu, Jianhua Nanjing Normal Univ Sch Comp Sci & Technol Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781728169262

Multi-label feature selection is a vital pre-processing step to reduce computational complexity, improve classification performance and enhance model interpretability, via selecting a discriminative subset of features from original high-dimensional features. Correlation-based feature selection (CFS) criterion measures the relevance between features and labels, and the redundancy among features, which has been combined with hill climbing and genetic algorithm to execute multi-label feature selection task. However, it is an open problem to search for more effective optimization tools for CFS. In this paper, through adding a mutation operation, we modify existing binary bat algorithm to build its mutation version (MBBA), to adjust the number of "1" components to be a fix size. Then a new multi-label feature selection approach is proposed via maximizing CFS criterion using MBBA, to select a fixed number of discriminative features. Our experiments on four data sets show that our proposed method is superior to three state-of-the-art approaches, according to four sample-based performance evaluation metrics for multi-label classification.

关键词： multi-label learning feature selection correlation-based criterion bat algorithm mutation operation

来源：评论

学校读者我要写书评

暂无评论

Discrete bat algorithm for Event Planning Optimization 43

Discrete Bat Algorithm for Event Planning Optimization

引用

43rd International Convention on Information, Communication and Electronic Technology (MIPRO)

作者： Delalic, S. Alihodzic, A. Tuba, M. Sebnanovic, E. Hasic, D. Univ Sarajevo Fac Sci Sarajevo Bosnia & Herceg Singidunum Univ Belgrade Serbia

ISBN: (纸本)9789532330991

Many public figures, companies and associations are planning events in different cities and at the same time have active profiles on social media. The planning process requires processing a large amount of data and different parameters when choosing the best event venue. Social media captures a large number of fan actions per day. This paper describes the process of selecting the most appropriate cities to organize events, aided by data collected from social media. The problem is defined as a combinatorial optimization problem. A modified metaheuristic bat algorithm was proposed, implemented, and described in detail to solve the problem. Although the original bat algorithm is designed to solve continuous optimization problems, the implemented bat algorithm is adapted to solve the defined problem. The algorithm is compared to the exhaustive search method for smaller instances, and to the greedy and genetic algorithm for larger instances. The algorithm was tested on benchmark data on cities in 20 European countries, as well as on real data collected from pages on the social network Facebook. bat algorithm has shown superior results compared to other techniques, both in time and in the quality of the solutions generated.

关键词： bat algorithm Discrete bat algorithm Event Planning Metaheuristic

来源：评论

学校读者我要写书评

暂无评论

Path Planning for Mobile Robot Based on Improved bat algorithm

引用

SENSORS 2021年第13期21卷 4389-4389页

作者： Yuan, Xin Yuan, Xinwei Wang, Xiaohu Harbin Engn Univ Coll Intelligent Syst Sci & Engn Harbin 150001 Peoples R China

bat algorithm has disadvantages of slow convergence rate, low convergence precision and weak stability. In this paper, we designed an improved bat algorithm with a logarithmic decreasing strategy and Cauchy disturbance. In order to meet the requirements of global optimal and dynamic obstacle avoidance in path planning for a mobile robot, we combined bat algorithm (BA) and dynamic window approach (DWA). An undirected weighted graph is constructed by setting virtual points, which provide path switch strategies for the robot. The simulation results show that the improved bat algorithm is better than the particle swarm optimization algorithm (PSO) and basic bat algorithm in terms of the optimal solution. Hybrid path planning methods can significantly reduce the path length compared with the dynamic window approach. Path switch strategy is proved effective in our simulations.

关键词： path planning bat algorithm dynamic window approach logarithmic decreasing strategy Cauchy disturbance

来源：评论

学校读者我要写书评

暂无评论

Design and Validation of bat algorithm-Based Photovoltaic System Using Simplified High Gain Quasi Boost Inverter

引用

ENERGIES 2021年第4期14卷 1086页

作者： Rajalakshmi, Mani Chandramohan, Sankaralingam Kannadasan, Raju Alsharif, Mohammed H. Kim, Mun-Kyeom Nebhen, Jamel Anna Univ Dept Elect & Elect Engn Coll Engn Guindy Chennai 600025 Tamil Nadu India Sri Venkateswara Coll Engn Dept Elect & Elect Engn Sriperumbudur 602117 Tamil Nadu India Sejong Univ Coll Elect & Informat Engn Dept Elect Engn 209 Neungdong Ro Seoul 05006 South Korea Chung Ang Univ Dept Energy Syst Engn 84 Heukseok Ro Seoul 156756 South Korea Prince Sattam bin Abdulaziz Univ Coll Comp Engn & Sci POB 151 Alkharj 11942 Saudi Arabia

Owing to the intermittent nature of renewable energy systems, an improved power extraction technique and modernized power modulators are to be designed to overcome power quality challenges. Attesting to this fact, this work aims to enhance the efficiency of the photovoltaic (PV) system using the bat algorithm (BA) and enhances the overall performance of the system using modified inverter topology. Specifically, a new power electronic modulator, i.e., a simplified high gain quasi-boost inverter (SHGqBI), is implemented to eliminate the downsides of the conventional system. The proposed inverter reduces the additional components that can condense the volume of the design with reduced conduction and switching losses. The combination of BA-based PV rated 250 W and novel inverter configuration pick the global peak power with enhanced power quality. Notably, BA extracts the maximum power from the panel meritoriously with about 98.8% efficiency. This is because BA uses the global input parameters to track the maximum power of the PV panel, whereas other conventional maximum power point tracking (MPPT) techniques used limited parameters. Further, the current and voltage total harmonic distortion (THD) of the proposed inverter are recorded, which show a commendable range of 2.7% and 10.2%, respectively. In addition, the efficiency of the inverter is found to be 97%. Consequently, the overall system efficiency is calculated and found to be 97.9%, providing greater advantages over a conventional system. The system is mathematically modelled using MATLAB/Simulink and validated through an experimental setup with the laboratory prototype model.

关键词： bat algorithm SHGqBI photovoltaic boost inverter total harmonic distortions

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：