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检索条件"主题词=Whale optimization algorithm"

共 1208 条记录，以下是301-310 订阅

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Feature Selection with The whale optimization algorithm and Artificial Neural Network

Feature Selection with The Whale Optimization Algorithm and ...

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2017 International Artificial Intelligence and Data Processing Symposium (IDAP)

作者： Canayaz, Murat Demir, Murat Van Yuzuncu Yil Univ Bilgisayar Muhendisligi Bolumu Van Turkey Mus Alparslan Univ Bilgisayar Muhendisligi Bolumu Mus Turkey

ISBN: (纸本)9781538618806

Feature selection is addressed an important problem in data mining. To be high dimension of the data obtained from the sources is encountered as an issue in many issues such as computation cost. For this reason, eliminating the unnecessary ones among these data and choosing the appropriate ones makes it possible to evaluate the information correctly. In this study, it is tried to suggest a method that can be used in feature selection on data sets. In this method, The whale optimization algorithm, which is one of the new meta-heuristic algorithms, is used to select appropriate features. Training with artificial neural networks takes place during the evaluation process of selected features. At the end of the training, the features that provide the minimum error value are selected. In the performance evaluation of the method, known data sets will be used and the results will be given in comparison with the Particle Swarm optimization method.

关键词： whale optimization algorithm feature selection artificial neural network

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An Enhanced Opposition-Based Golden-Sine whale optimization algorithm 7th

An Enhanced Opposition-Based Golden-Sine Whale Optimization ...

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7th International Conference on Cognitive Computing (ICCC) Held as Part of the Services Conference Federation Meeting (SCF)

作者： Lu, Yong Yi, Chao Li, Jiayun Li, Wentao Minzu Univ China Sch Informat Engn Beijing Peoples R China

ISBN: (纸本)9783031516702;9783031516719

The whale optimization algorithm is an ingenious method conceived by researchers, drawing inspiration from the feeding behavior of humpback whales. Characterized by its simple structure, limited parameters, high efficiency, and robust optimization capacity, WOA has been extensively applied across multiple domains to address various challenges. Nonetheless, it has been found that the algorithm demonstrates low global exploration capability, inadequate search precision, and susceptibility to local optima entrapment. Many enhancements have been suggested in the literature, with Opposition-Based Learning emerging as a particularly effective technique for improving the quality of the initial population. In the present study, we put forth the Enhanced Opposition-Based strategy, which integrates supplementary constraints into the existing Opposition-Based Learning framework, generating a more refined initial population. Furthermore, we introduce the Golden Sine algorithm to modify the optimization approach of WOA, fostering an equilibrium between global exploration and exploitation abilities. In our evaluation, the proposed algorithm is assessed on nine classic benchmark functions with a dimensionality of 500, and compared with the original WOA, An enhanced whale optimization algorithm (eWOA), and the Elite Opposition-Based Golden-Sine whale optimization algorithm (EGolden-SWOA). The results exemplify the superior performance of our proposed algorithm, underscoring its potential application in the optimization of truss structure design problems, the results indicate that ESWOA outperforms other enhanced algorithms, such as eWOA and EGolden-SWOA, in terms of its performance in engineering optimization. This signifies that ESWOA can be effectively applied to engineering optimization problems.

关键词： whale optimization algorithm Opposition-Based Learning Golden Sine algorithm engineering optimization

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Comparative Parameter Estimation of Single Diode PV-Cell Model by Using Sine-Cosine algorithm and whale optimization algorithm 6

Comparative Parameter Estimation of Single Diode PV-Cell Mod...

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6th International Conference on Electrical and Electronics Engineering (ICEEE)

作者： Aydin, Omer Gozde, Haluk Dursun, Mahir Taplamacioglu, M. Cengiz Gazi Univ Fac Engn Dept Elect & Elect Engn Ankara Turkey Natl Def Univ Turkish Mil Acad Elect & Commun Engn Dept Ankara Turkey

ISBN: (纸本)9781728139104

The share of photovoltaic energy systems in electricity production is increasing day by day. Photovoltaic systems are typically modeled as PV-cell circuit when using in power system analysis. The selection of the parameters used in the model is crucial because how close the model outputs are to reality depends on true estimation of these parameters. These parameters are also important for efficiency and maximum power tracking. Due to the increase in electricity generation with solar energy, the problem of estimation of these parameters has become a widely studied subject in recent years. In this study, the parameters of PV-cell are estimated using whale optimization algorithm (WOA) and Sine-Cosine algorithm (SCA) and compared with the related literature.

关键词： photovoltaic cells whale optimization algorithm sine-cosine algorithm parameter estimation

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Active Disturbance Rejection Control of Quadrotor UAV based on whale optimization algorithm 19

Active Disturbance Rejection Control of Quadrotor UAV based ...

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19th IEEE International Conference on Mechatronics and Automation (IEEE ICMA)

作者： Liu, Xinpeng Gao, Qiang Ji, Yuehui Song, Yu Liu, Junjie Tianjin Univ Technol Sch Elect Engn & Automat Tianjin Peoples R China

ISBN: (数字)9781665408530

ISBN: (纸本)9781665408530;9781665408523

This paper aims at the problems of nonlinearity, underactuated, strong coupling, and difficult controller parameter tuning in the control process of quadrotor UAV, PID controller and ADRC are designed to control the quadrotor UAV, and the controller parameters are optimized by the whale optimization algorithm. Firstly, the ADRC is designed to control the attitude loop of the quadrotor UAV. The Extended State Observer (ESO) is designed for yaw, pitch, and roll channels to observe and compensate the internal uncertainties and external disturbances in real-time, and to realize decoupling control. Secondly, in the position control system, the PID controller is used to realize the stable tracking of position variables. Finally, the whale optimization algorithm (WOA) is designed to optimize the Active Disturbance Rejection Controller and PID controller for the quadrotor UAV, which has many controller parameters and is difficult to get the optimal control effect. In this method, the parameters of the controller are taken as the objective of WOA optimization to achieve the optimal control effect. The simulation results show that the WOA optimized controller has a smaller overshoot and faster adjustment time compared with human tuning parameters.

关键词： PID Active Disturbance Rejection Controller whale optimization algorithm Quadrotor UAV Parameter optimization Trajectory tracking

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A modified whale optimization algorithm based on Chaos Initialization and Regulation Operation 38

A modified Whale Optimization Algorithm based on Chaos Initi...

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38th Chinese Control Conference (CCC)

作者： Jiang Ruiye Chao Tao Wang Songyan Yang Ming Harbin Inst Technol Harbin 150001 Peoples R China

ISBN: (纸本)9789881563972

A rising meta-heuristic swarm intelligent computation algorithm, the whale optimization algorithm (WOA), which has been proved competitive with other intelligent optimization algorithms in solving different optimization problems. To accelerate the convergence rate of WOA, this paper has proposed a new improved whale optimization algorithm, called Chaos Regulation whale optimization algorithm (CRWOA). The chaotic map generator composed with three kinds of chaotic maps has been used to initialize the population. Furthermore, Cauchy distribution and Gauss distribution are introduced to regulate the position in each iteration. To analyze the superiority of CRWOA further, ten single-objective benchmark test functions are chosen. Through the comparison and analysis of the optimal results, CRWOA is demonstrated superior in general. It has faster convergence speed and better results than the other algorithms when less iteration number, less population quantity and wider ranges of variables are set.

关键词： Benchmark functions Chaotic map Computation intelligence Continuous probability distribution whale optimization algorithm

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Parametric optimization of CNC-drilling of Inconel 718 with cryogenically treated drill-bit using Taguchi-whale optimization algorithm 2nd

Parametric optimization of CNC-drilling of Inconel 718 with ...

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2nd International Conference on Functional Material, Manufacturing and Performances (ICFMMP)

作者： Sahoo, Aditya Kumar Jeet, Siddharth Bagal, Dilip Kumar Barua, Abhishek Pattanaik, Ajit Kumar Behera, Niranjan Govt Coll Engn Dept Mech Engn Bhawanipatna Odisha India BPUT Ctr Adv Post Grad Studies Dept Mech Engn Rourkela Odisha India Govt Coll Engn Dept Elect Engn Bhawanipatna Odisha India

This study investigates the drilling operation on Inconel 718 superalloy by using cryogenic treated drill bit. Thrust force, torque and surface roughness are analyzed to understand the effects of the cryogenic condition during CNC drilling operation. Taguchi's methodology has been employed for planning of experiments. Drill bits are conditioned under two different environment i.e. cryogenically treated with single tempered and cryogenically treated with double tempered. The process parameters are optimized by using whale optimization algorithm for obtaining minimized surface roughness along with maximization of torque and thrust force during drilling operation. The ANOVA results show that feed rate is the most contributing significant factor for thrust for its maximization while spindle speed is the most contributing significant factor for torque for its maximization. Also, tool condition is the most contributing significant factor for surface roughness for its minimization. Lastly, confirmatory test were conducted to find out the significance of the predicted values obtained using the optimization methods. Copyright (c) 2021 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the 2nd International Conference on Functional Material, Manufacturing and Performances

关键词： Cryogenic Tempering Inconel 718 CNC-drilling Taguchi method whale optimization algorithm

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WOAMSA: whale optimization algorithm for Multiple Sequence Alignment of Protein Sequence 1

引用

International Conference on Computational Vision and Bio-Inspired Computing (ICCVBIC)

作者： Kumar, Manish Kumar, Ranjeet Nidhya, R. MITS Dept CSE Madanapalle India

ISBN: (数字)9783030372187

ISBN: (纸本)9783030372187;9783030372170

In the past few years, the Multiple Sequence Alignment (MSA) related problems has gained wide attractions of scientists and biologists as it is one of the major tools to find the structural and behavioral nature of Biomolecules. Furthermore, MSA can also be utilized for gene regulation networks, protein structure prediction, homology searches, genomic annotation or functional genomics. In this paper, we purpose a new nature and bio-inspired algorithm, known as the whale optimization algorithm for MSA (WOAMSA). The algorithm works on the principle of bubble-net hunting nature of the whale with the help of objective function we tried to solve the MSA problems of protein sequences. In order to focus on the effectiveness of the presented approach, we used BALiBASE benchmarks dataset. At the last, we have compared the obtained result for WOAMSA with other standard methods mentioned in the literature. After comparison, it was concluded that the presented approach is better (in terms of obtained scores) when compared with other methods available in the considered datasets.

关键词： Proteins Bioinformatics whale optimization algorithm Multiple Sequence Alignment

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Image Enhancement based on whale optimization algorithm 15

Image Enhancement based on Whale Optimization Algorithm

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15th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET)

作者： Ye, Zhiwei Wang, Fengwen Kochan, Roman Hubei Univ Technol Sch Comp Sci Wuhan Peoples R China Univ Bielsko Biala Dept Comp Sci & Automat Bielsko Biala Poland Lviv Polytech Natl Univ Dept Specialized Comp Syst Lvov Ukraine

ISBN: (纸本)9781728155661

The digital image technology is the most widely used in various fields, especially in medical imaging. Digital image technology can effectively improve the efficiency of medical image processing and ensure the accuracy of clinical diagnosis. This paper studies whale optimization algorithm (WOA) to optimize the optimal value of Gamma correction in image enhancement. In the process of searching for the optimal solution, the WOA is an efficient algorithm, which has the characteristics of fast convergence and high precision. In order to present the detailed information of medical image, WOA is applied to search the optimal value of Gamma correction.

关键词： whale optimization algorithm Ant Lion algorithm Gamma correction Image enhancement

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Extending the whale optimization algorithm with Chaotic Local Search 7

Extending the Whale Optimization Algorithm with Chaotic Loca...

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7th International Conference on Soft Computing and Machine Intelligence (ISCMI)

作者： Rohr, Nicolas Ruggli, Oliver Hanne, Thomas Dornberger, Rolf Univ Appl Sci & Arts Northwestern Switzerland Olten Switzerland

ISBN: (纸本)9781728175591

The whale optimization algorithm (WOA) is a recently introduced metaheuristic that has shown a promising performance in solving optimization problems. To further improve the search performance of WOA, the Chaotic Local Search (CLS) mechanism is incorporated into WOA. Ten different chaotic maps are investigated to give insights into the influence of CIS in the WOA. The goal is to compare th e performance of the whale optimization algorithm with Chaotic Local Search (WOACLS) with the standard WOA and the Chaotic WOA (CWOA) by applying them to twenty wellknown benchmark functions. Results show that the performance of WOACLS depends on both, the characteristics of the embedded chaotic map and the properties of the search landscape of the optimization problems considered.

关键词： whale optimization algorithm chaos map: chaotic local search WOA CWOA WOACLS

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Decision Tree with whale optimization algorithm (DT-WOA) for QoS-based IoT Service Composition 1

Decision Tree with Whale Optimization Algorithm (DT-WOA) for...

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1st International Conference on Electrical, Computer, Telecommunication and Energy Technologies

作者： Ouhadda, Souhila Ait Hacene Sadouki, Samia Chibani Tari, Abdelkamel Univ Bejaia LIMED Lab Fac Exact Sci Bejaia 06000 Algeria Higher Sch Sci & Technol Comp & Digital ESTIN Fac Exact Sci Lab LITAN LIMED Lab RN 75 Amizour Bejaia 06300 Algeria

ISBN: (纸本)9798350388497;9798350388480

From smart homes to smart cities, the Internet of Things (IoT) has revolutionized our lives by connecting billions of devices into an interconnected network. Each smart device offers specific functions, such as remote door unlocking or sending alerts, which we call IoT services. To meet the complex needs of users, combining multiple atomic IoT services is required, as a single service is often insufficient. The increasing number of IoT services offering similar functionality makes service composition based on Quality of Service (QoS) attributes more challenging. To address this issue, we propose a DT-WOA approach combining a Decision Tree (DT) with the whale optimization algorithm (WOA). We use DT-WOA to find a close-to-optimal solution that meets the QoS user requirements. Simulation results indicate that DT-WOA outperforms the original WOA in terms of fitness value by effectively reducing the search space.

关键词： Quality of Service Service Composition Internet of Things Decision Tree whale optimization algorithm Service Selection

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