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检索条件"主题词=whale optimization algorithm"

共 1217 条记录，以下是331-340 订阅

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Turkey Long-Term Energy Consumption Prediction Using whale optimization algorithm 29

Turkey Long-Term Energy Consumption Prediction Using Whale O...

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29th IEEE Conference on Signal Processing and Communications Applications (SIU)

作者： Babaoglu, Merve Haznedar, Bulent Mardin Artuklu Univ Bilgisayar Programciligi Mardin Turkey Gaziantep Univ Bilgisayar Muhendisligi Gaziantep Turkey

ISBN: (纸本)9781665436496

Energy is one of the most important topics for the sustainable development of countries. Due to the fact that the energy used can be depleted, it imports many energy sources, and environmental factors, it is of great importance for Turkey to predict how much energy needs may be in the future. In this study, whale optimization algorithm (BOA) was preferred from heuristic algorithms in order to be able to estimate Turkey's energy demand until 2040. In order to determine the performance of the whale optimization algorithm, the results were compared with the genetic algorithm (GA). All models are arranged linearly and squared and the result is obtained. Data for independent variables such as gross domestic product (GDP), population, imports and exports affecting energy demand were used between 1990 and 2019. Modeling of the past 30 years has been provided to calculate the accuracy of the results. After obtaining the most suitable model, calculations were made according to 4 different scenarios for the next 20 years.

关键词： whale optimization algorithm Genetic algorithm Turkey Energy Consumption Predict

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Economic dispatch using stochastic whale optimization algorithm

Economic dispatch using stochastic whale optimization algori...

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International Conference on Innovative Trends in Computer Engineering (ITCE)

作者： Mohamed, FatmaAlzahra Abdel-Nasser, Mohamed Mahmoud, Karar Kamel, Salah Aswan Univ Dept Elect Engn Aswan 81542 Egypt

ISBN: (纸本)9781538608791

Economic dispatch aims to determine the optimal generated power from the generation units to meet the required load at the lowest fuel cost. In this paper, a stochastic whale optimization (SWO) method is proposed to solve the economic dispatch problem. whale optimization algorithm is enhanced using mutation and crossover operators. To test the proposed method two systems (3 and 10 generating units) are tested. We compare the proposed SWO algorithm with whale optimization algorithm, artificial bee colony algorithm, dragonfly algorithm, ant lion algorithm, gray wolf optimization, and whale optimization algorithm with mutation only. The obtained results demonstrate the high efficiency of the proposed method compared with the other methods.

关键词： Economic Dispatch Smart Grid whale optimization algorithm

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Stabilization of a reduced order inverted pendulum by using whale optimization algorithm 4

Stabilization of a reduced order inverted pendulum by using ...

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4th International Conference on Computing Communication Control and Automation (ICCUBEA)

作者： Guha, Dipayan Singh, Shivam Kumar Sharma, Shubham Kumar Ranjan, Ravi Kant Priya, Swati Ghosh, Arnab Motilal Nehru Natl Inst Technol Elect Engn Dept Allahabad Uttar Pradesh India Dr B C Roy Engn Coll Elect Engn Dept Durgapur W Bengal India Natl Inst Technol Elect Engn Dept Rourkella Odisha India

ISBN: (纸本)9781538652572

In this paper, an attempt has been made to develop an efficient control algorithm for the stabilization of an inverted pendulum. A novel stochastic optimization technique namely whale optimization algorithm (WOA) is employed to search the optimum settings of proportional-integral-derivative controller with derivative filter (PIDF). The proposed WOA mimics bubble net hunting mechanism of humpback whales in nature. The main advantage of this algorithm is that only population size and maximum iteration count are required for its operation. Logarithmic approximation and time-moments have been adopted to formulate the reduced order model (ROM) of inverted pendulum. The results presented in this paper clearly show that proposed control algorithm with ROM exhibit satisfactory outputs and effectively increases the stability margin of inverted pendulum.

关键词： Inverted pendulum whale optimization algorithm Logarithmic approximation Time-moments Transient analysis

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Price Penalty Factors based Approach for Emission Constrained Economic Dispatch Problem Solution using whale optimization algorithm 1

Price Penalty Factors based Approach for Emission Constraine...

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1st IEEE International Conference on Power Electronics, Intelligent Control, and Energy Systems (ICPEICES)

作者： Trivedi, Indrajit N. Jangir, Narottam Jangir, Pradeep Pandya, Mahesh H. Bhesdadiya, R. H. Kumar, Arvind Govt Engn Coll Dept Elect Engn Gandhinagar Gujarat India Lukhdhirji Engn Coll Dept Elect Engn Morbi Gujarat India SS Engn Coll Dept Elect Engn Bhavnagar Gujarat India

ISBN: (纸本)9781467385879

In The main ambition of utility is to provide continuous reliable supply to customers, satisfying power balance, transmission loss while generators are allowed to be operated within rated limits. Meanwhile, achieve this purpose emission value and fuel cost should be as less as possible. An allowable deviation in fuel cost and feasible tolerance in fuel cost has been called emission constrained economic dispatch (ECED) problem. A new nature-inspired whale optimization algorithm (WOA) is based on concept of bubble-net hunting strategy is applied to solve ECED problem. ECED is a multi-criteria problem can transformed to single criteria using price penalty factor method. In this paper quadratic function together with emission value and fuel cost are considered as individual objective makes it multi-criteria problem. The effect of six penalty factors like "Min-Max", "Max-Max", "Min-Min", "Max-Min", "Average", "Common" price penalty factors and emission value of various pollutants gases exhalation are included. The emission constrained economic dispatch (ECED) problem is analysed for an IEEE-30 Bus system with six operational generator units. Results prove capability of WOA in solving ECED problem with different penalty factors.

关键词： whale optimization algorithm Bubble-net Hunting Strategy Emission Constrained Economic Dispatch Fuel Cost Emission Value

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Analysis of Different Binarization Techniques within whale optimization algorithm

Analysis of Different Binarization Techniques within Whale O...

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Innovations in Intelligent Systems and Applications Conference (ASYU)

作者： Golcuk, Ilker Ozsoydan, Fehmi Burcin Durmaz, Esra Duygu Izmir Bakircay Univ Dept Ind Engn Izmir Turkey Dokuz Eylul Univ Dept Ind Engn Izmir Turkey Gazi Univ Dept Ind Engn Ankara Turkey

ISBN: (纸本)9781728128689

In this study, whale optimization algorithm (WOA), which is a recently proposed swarm intelligence-based algorithm, has been used to solve binary optimization problems. As the WOA algorithm has been developed for optimizing realvalued functions, binary versions of the WOA algorithm have been adopted for the binary optimization problems. The performance of modulation-, normalization-, s-shaped transfer function-, and angle modulation-based binarization approaches are compared. The proposed algorithms tested on the well-known benchmark problems, namely one-max, plateau, deceptive, and royal road. Our computational experiments show that angle modulation and normalization-based binarization approaches give the best results, and binary WOA is promising and has potential to handle difficult binary optimization problems.

关键词： binary optimization binarization techniques whale optimization algorithm

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Optimal PID Controller Design of DC-DC Buck Converter using whale optimization algorithm

Optimal PID Controller Design of DC-DC Buck Converter using ...

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International Conference on Artificial Intelligence and Data Processing (IDAP)

作者： Hekimoglu, Baran Ekinci, Serdar Kaya, Serhat Batman Univ Dept Elect & Elect Engn Batman Turkey Batman Univ Dept Comp Engn Batman Turkey

ISBN: (纸本)9781538668788

This paper presents a novel design method to determine optimal proportional-integral-derivative (PID) controller parameters of a DC-DC buck converter using the whale optimization algorithm (WOA). The simplicity of the proposed algorithm provides fast and high quality tuning of optimum PID controller parameters effectively. The performance of the proposed WOA-based PID controller is validated using a time domain performance index. From simulation results, the proposed method compared to the genetic algorithm was found more efficient in improving the transient response of Buck converter.

关键词： whale optimization algorithm DC-DC buck converter output voltage regulation PID controller parameter tuning

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A Backbone whale optimization algorithm Based on Cross-stage Evolution 13th

A Backbone Whale Optimization Algorithm Based on Cross-stage...

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13th International Conference on Swarm Intelligence (ICSI)

作者： Yang, Xin Wang, Limin Zhang, Zhiqi Han, Xuming Yue, Lin Jinan Univ Guangzhou Peoples R China

ISBN: (纸本)9783031096778;9783031096761

The swarm intelligent algorithms (SIs) are effective and widely used, while the balance between exploitation and exploration directly affects the accuracy and efficiency of algorithms. To cope with this issue, a backbone whale optimization algorithm based on cross-stage evolution (BWOACS) is proposed. BWOACS is mainly composed of three parts: (1) adopts the density peak clustering (DPC) method to actively divide the population into several sub-populations, generates the backbone representatives (BR) during backbone construction stage;(2) determines the deviation placement (DP) by constructing the co-evolution operators (CE), the search space expansion operators (SE) and the guided transfer operators (GT) during bionic evolution strategy stage;(3) realises the bionic optimisation through DP during backbone representatives guiding co-evolution stage. To verify the accuracy and performance of BWOACS, we compare BWOACS with other variants on 9 IEEE CEC 2017 benchmark problems. Experimental results indicate that BWOACS has better accuracy and convergence speed than other algorithms.

关键词： whale optimization algorithm Density peak clustering Bionic evolution strategy

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Improvement whale optimization algorithm Based on Mixed Strategy 15

Improvement Whale Optimization Algorithm Based on Mixed Stra...

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15th International Conference on Advanced Computational Intelligence (ICACI)

作者： Liu Yujia Tang Feng Chen Xin Jiangxi Coll Applicat Sci & Technol Sch Intelligent Mfg Engn Nanchang 330000 Jiangxi Peoples R China Jiangxi Univ Sci & Technol Sch Informat Engn Ganzhou 341000 Peoples R China Zhejiang Normal Univ Coll Math & Comp Sci Jinhua 321004 Zhejiang Peoples R China

ISBN: (纸本)9798350321456

As the original whale optimization algorithm (WOA) has the drawback of falling into local extremes, it also fails to meet the expectations in terms of convergence effect. An improved whale optimization algorithm (HWOA) based on a hybrid strategy was proposed. First, the proposed algorithm is initialized based on the Zaslayskii chaotic map to obtain a population with better ergodicity;second, The elite search base strategy is used to improve the global optimization ability of the algorithm and increase the probability of jumping out of the local extreme value;Finally, by introducing an adaptive variable speed strategy, the search ability and development capabilities of the whale optimization algorithm are effectively coordinated while retaining the advantages of the algorithm. The improved whale optimization algorithm is tested against other algorithms on 10 benchmark functions. The final results demonstrate the effectiveness of the HWOA algorithm improvement strategy and outperforms other improvement algorithms in terms of effectiveness.

关键词： whale optimization algorithm chaotic mapping elite search pool adaptive adjustment factor

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An Orthogonal Learning Design whale optimization algorithm with Clustering Mechanism 24

An Orthogonal Learning Design Whale Optimization Algorithm w...

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24th IEEE International Conference on Computer Supported Cooperative Work in Design (IEEE CSCWD)

作者： Zhao, Fuqing Bao, Haizhu Liu, Huan Lanzhou Univ Technol Sch Comp & Commun Technol Lanzhou Peoples R China

ISBN: (纸本)9781728165974

In this paper, an orthogonal learning (OL) design whale optimization algorithm (WOA) with clustering mechanism, named OLWOA, is proposed to solve the complex continuous problems. In the proposed algorithm, the OL, as an effective strategy to utilize prior search information (experience), is utilized to overcome the disadvantages of the basic WOA, which converges slowly and falls into local optimum easily. The clustering-based mechanism guides the humpback whales to search toward an interesting area by propagating the information of good solutions from one cluster to another cluster. The experimental results reveal the effectiveness and significance of the OL and the clustering-based learning mechanism in the proposed algorithm.

关键词： whale optimization algorithm Orthogonal learning design Clustering mechanism swarm intelligence

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Wearable 5-Gigahertz Wi-Fi Antenna Design Using whale optimization algorithm 14

Wearable 5-Gigahertz Wi-Fi Antenna Design Using Whale Optimi...

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14th European Conference on Antennas and Propagation (EuCAP)

作者： Boursianis, Achilles D. Koulouridis, Stavros Georgoulas, Dimitrios Goudos, Sotirios K. Aristotle Univ Thessaloniki Dept Phys Thessaloniki 54124 Greece Univ Patras Elect & Comp Engn Dept Patras Greece

ISBN: (数字)9788831299008

ISBN: (纸本)9788831299008

In this paper, we design an antenna for wearable wireless applications. The proposed antenna is a planar inverted- F antenna (PIFA) for operation at 5 GHz. The antenna design procedure is accomplished using a new nature inspired algorithm, the whale optimization algorithm. Numerical results exhibit the applicability and validity of the proposed design framework.

关键词： wearable antennas whale optimization algorithm nature-inspired algorithms printed inverted-F antenna

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