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2nd International Conference on Energy, Power and Environment - Towards Smart Technology (ICEPE)

作者： Saha, Arindita Saikia, Lalit Chandra Tasnin, Washima Rajbongshi, Rumi Saha, Debdeep Natl Inst Technol Silchar Dept Elect Engn Silchar India

ISBN: (纸本)9781538647691

This work focuses on incorporation of distribution generation (DG) units in unequal three area interconnected automatic generation control (AGC) system with diversified sources. The particular system is associated with appropriate value of generation rate constraint for realistic approach. A cascade combination of integer order proportional-integral-derivative with filter and fractional order integral derivative (PIDN-FOID) is utilized for study. The controller gains plus parameters are obtained using whale optimization algorithm. The performance of PIDN-FOID controller is evaluated against classical controllers. Analyses show that inclusion of DG units provides noticeable improvement on system dynamics. In AGC various energy storage devices are used in order to mitigate inter-area oscillations. Here, energy storage device redox flow battery (RFB) is incorporated in all areas. Observation reflects that inclusion of RFB improves system dynamics. Sensitivity analysis is performed for increased value of step load perturbation in presence of DG units as well as RFB.

关键词： Automatic generation control distributed generation (DG) PIDN-FOID controller redox flow battery whale optimization algorithm

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Multi-sensor image fusion based on contrast and directional features optimization

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INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS 2018年第12期14卷

作者： Jin, Haiyan Zhang, Meng Xiao, Zhaolin Li, Yaning Xian Univ Technol Sch Comp Sci & Engn Xian 710048 Shaanxi Peoples R China Shaanxi Key Lab Network Comp & Secur Technol Xian Shaanxi Peoples R China

Multi-sensor image fusion is always an important and opening problem, which can enhance visual quality and benefit some social security applications. In this article, we use contrast pyramid to decompose visible and infrared images, respectively, and the directional filter banks are applied to obtain multiple directional sub-band image features. Then, we compute the decomposition coefficients of visible and infrared images using a low-pass filter on the decomposed data;and finally, we introduce the whale optimization algorithm to search optimal coefficients to reconstruct the final fusion image. The experiments are conducted on multiple datasets with subjective and objective comparisons, in which the qualitative and quantitative analyses indicate the validity of the proposed method.

关键词： Image fusion multi-sensors directional features optimization whale optimization algorithm

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Compound Jamming Airspace Planning via TWOA

Compound Jamming Airspace Planning via TWOA

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International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC)

作者： Wang, Qinghao Wang, Linlin Yao, Dengkai Air Force Engn Univ Grad Coll Xian Shaanxi Peoples R China Henan Normal Univ Comp & Informat Engn Coll Xinxiang Henan Peoples R China Air Force Engn Univ Air Traff Control & Nav Coll Xian Shaanxi Peoples R China

ISBN: (纸本)9781538660577

As traditional radar jamming methods face severe challenges, a new strategy for forwarding jamming using chaff was proposed. Its principle was introduced, its interference performance was calculated, and compound jamming effect and safety of jammer were calculated. A space model for longdistance support of compound jamming was established. The pseudo-random and ergodicity of the Tent chaotic sequence were introduced into the whale optimization algorithm to reduce the probability of the whale optimization algorithm falling into a local optimum, which was used to solve the model. Simulation verification was carried out and relevant airspace layout was obtained. Simulation shows that the model built is scientific and effective.

关键词： compound jamming Tent chaotic sequence whale optimization algorithm

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Multi-objective whale optimization

Multi-objective Whale Optimization

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IEEE Region 10 Conference (TENCON)

作者： Kumawat, Ishwar Ram Nanda, Satyasai Jagannath Maddila, Ravi Kumar Malaviya Natl Inst Technol Dept Elect & Commun Engn Jaipur 302017 Rajasthan India

ISBN: (纸本)9781509011346

This paper deals with designing a multi-objective algorithm based on recently proposed whale optimization algorithm (WOA), termed as MOWOA. The original WOA algorithm is popular among the researchers due to the encircling moments of agents (Humpback whales) in the search space which provides proper balance among the exploration and exploitation, faster convergence and lessor number of parameters. The proposed multi-objective version posses all the above benefits of the original algorithm, in addition it reveals accurate convergence to the true Pareto fronts and maintain effective diversity among the solutions. The performance is demonstrated on six unconstrained bi-objective functions of IEEE CEC 2009. The obtained results are compared with that achieved by multi-objective Grey Wolf optimization (MOGWO), multi-objective Particle Swarm optimization (MOPSO), multi-objective Evolutionary algorithm based on Decomposition(MOEA/D).

关键词： whale optimization algorithm MOGWO MOPSO MOEA/D Pareto front

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A WOA-based algorithm for parameter optimization of support vector regression and its application to condition prognostics 36

A WOA-based algorithm for parameter optimization of support ...

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第36届中国控制会议

作者： LI Sai FANG Huajing School of Automation Key Laboratory of Image Processing and Intelligent ControlMinistry of EducationHuazhong University of Science and Technology

ISBN: (纸本)9781538629185

Condition monitoring is very important for system safety and condition-based *** series prediction capabilities of machine learning like support vector regression(SVR) can be utilized for ***,choosing optimal parameters for SVR is an important step in SVR model design,which heavily affects the performance of ***,a whale optimization algorithm(WOA) based algorithm is proposed for SVR parameters *** proposed algorithm has been evaluated through some benchmark ***,the proposed method with moving window technology is used to condition prognostics of the Tennessee Eastman *** and engineering application show that the SVR-WOA method is effective,by noting that the computation time is shortened in some application scenarios.

关键词： Support vector regression whale optimization algorithm Parameter optimization Condition prognostics

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Optimized weighted feature voting technique for content-based image retrieval

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JOURNAL OF ELECTRONIC IMAGING 2018年第5期27卷 053017-053017页

作者： Elhady, Walaa E. Alsammak, Abdelwahab K. El-Mashad, Shady Y. October 6 Univ Fac Engn Cairo Egypt Benha Univ Fac Engn Shoubra Egypt

A content-based image retrieval system is proposed using an optimized weighted feature voting technique with multifeatures and multidistance measures. The proposed system consists of two phases: enrollment phase and querying phase. In enrollment phase, six features have been extracted from each enrollment image. These features are color histogram, edge histogram, edge direction histogram, hierarchical annular histogram, Gabor filter, and co-occurrence matrix. The extracted features are weighted, and feature weights are optimized using the four optimization techniques. Particle swarm optimization, ant lion optimizer, bird swarm algorithm, and whale optimization algorithm are applied and compared to decide the suitable technique. In querying phase, the same features are extracted from the query image and comparing these features to the extracted features from the database images through the matching measures. Three distance measures have been used and compared for the matching process: histogram intersection, Euclidean distance, and cosine distance. Based on these distances and the feature weights, the class of the query image is identified using the weighted feature voting mechanism. Finally, the related images are retrieved based on the feature that returned the maximum number of images in the identified class. For the validation and performance evaluations of the proposed system;Wang, Caltech101, and UW datasets are used. The experimental results show that the proposed method achieves improved precision in comparison with existing methods with 93% for Wang database, 92% for UW database, and 94% for Caltech101 database. (C) 2018 SPIE and IS&T.

关键词： content-based image retrieval weighted feature voting particle swarm optimization bird swarm optimization ant lion optimizer whale optimization algorithm

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A proposed whale Search algorithm with Adaptive Random Walk 13

A proposed Whale Search Algorithm with Adaptive Random Walk

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13th IEEE International Conference on Intelligent Computer Communication and Processing (ICCP)

作者： Emary, E. Zawbaa, Hossam M. Salam, Mustafa Abdul Cairo Univ Fac Comp & Informat Giza Egypt Arab Open Univ Fac Comp Studies Cairo Egypt Beni Suef Univ Fac Comp & Informat Bani Suwayf Egypt Babes Bolyai Univ Fac Math & Comp Sci Cluj Napoca Romania Benha Univ Fac Comp & Informat Banha Egypt

ISBN: (纸本)9781538633687

In this paper, a variant of the recently introduced whale optimization algorithm (WOA) was proposed based on adaptive switching of random walk per individual search agent. WOA is recently proposed bio-inspired optimizers that employ two different random walks. The original optimizer stochastically switches between the two random walk at each iteration regardless of the search agents performance and regardless of the fitness terrain around it. In the proposed adaptive walk whale optimization algorithm (AWOA), an adaptive switching between the two random walk is recommended based on the agent's performance. Moreover, a random explorative switch of the walk is applied to allow search agents to try different walks. The proposed AWOA was benchmarked using 29 standard test functions with uni-modal, multi-modal, and composite test functions. Performance over such functions proves the capability of the proposed variant to outperform the original WOA.

关键词： whale optimization algorithm Adaptive random walk Adaptive whale optimization algorithm Bio-inspired optimization Evolutionary Computation

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Bubble-Net Hunting Strategy of whales based Optimized feature selection for E-mail Classification 2

Bubble-Net Hunting Strategy of Whales based Optimized featur...

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2nd International Conference for Convergence in Technology (I2CT)

作者： Saidala, Ravi Kumar Devarakonda, Naga Raju Acharya Nagarjuna Univ Dept Comp Sci & Engn Guntur 522510 Andhra Pradesh India LBR Coll Engn & Technol Dept Informat Technol Mylavaram 521230 Andhra Pradesh India

ISBN: (纸本)9781509043071

Spam E-mailis a kind of electronic spam in which unsolicited messages are sent by E-mail. It is the most severe problem world-wide for decades. One of the best approach to identify spam E-mails is filtering E-mails by classification. In many applications feature selection is the most widely used and essential task in many classification techniques to reduce the dimensionality of feature space. In this paper a Nature Inspired Meta-Heuristic algorithm, that exploits the SVM principles for finding optimized structures of the Enron-Spam dataset having high similarity, is proposed. We adopted the WOA to obtainan optimal feature subset for E-mail classification. Four different kernel functions are exploited, that includes Linear, Quadratic, Polynomial and RBF in classification to test the best kernel function for SVM. Different evaluation measurements such as Precision, Accuracy, Recall and F-measureare calculated to find the performance of the proposed technique. The investigated results are analysed and compared with those from other techniques published in spam E-mails filtering. All the analysed and compared results show that proposed technique is very competitive for E-mail classification.

关键词： whale optimization algorithm Feature Selection SVM E-mail Spam

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Congestion Mitigation Considering Solar Electric Vehicle: A Possible Solution for Today's Electricity Market

Congestion Mitigation Considering Solar Electric Vehicle: A ...

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IEEE International Conference on Technological Advancements in Power and Energy (IEEE TAP Energy) - Exploring Energy Solutions for an Intelligent Power Grid

作者： Gope, Sadhan Mitra, Rituparna Goswami, Arup Kumar Tiwari, Prashant Kumar Mizoram Univ Dept Elect Engn Aizawl Mizoram India Natl Inst Technol Silchar Dept Elect Engn Silchar Assam India

ISBN: (纸本)9781538640210

Congestion management is one of the most important task in the modern power system. Considering the solar electric vehicle (SEV), generator rescheduling based congestion management approach is proposed here to mitigate the transmission congestion. Generator sensitivity factor (GSF) with whale optimization algorithm (WOA) is applied here to find the rescheduling amount and congestion cost of the system. The optimal location of the electric vehicle (EV) charging station is found by using bus sensitivity factor (BSF). To analyze the proposed congestion management approach, WOA algorithm is tested with modified IEEE 30 bus system. To validate the obtained results with WOA algorithm, particle swarm optimization (PSO) and ant lion optimizer (ALO) algorithms are also used in this paper. The obtained results prove the effectiveness of utilization of SEV for minimizing the active power rescheduling amount, active power loss and congestion cost of the system.

关键词： Bus sensitivity factor Generator sensitivity factor Solar electric vehicle whale optimization algorithm

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Optimal Placement and Sizing of Multiple Active Power Filters for Radial Distribution System Using Grey Wolf Optimizer 7

Optimal Placement and Sizing of Multiple Active Power Filter...

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7th International Conference on Power Systems (ICPS)

作者： Lakum, Ashokkumar Mahajan, Vasundhara Sardar Vallablibhai Natl Inst Technol Surat Elect Engn Dept Surat India

ISBN: (纸本)9781538617892

This paper presents, grey wolf optimizer (GWO) algorithm to solve a constrained nonlinear optimization problem of optimal placement and sizing of multiple active power filters (OPSMAPFs) for radial distribution system (RDS). It is a nature inspired stochastic algorithm. It has balanced exploration and exploitation characteristics. Minimization of the current of APF is taken as an object with three inequality constraints. To evaluate the performance of GWO algorithm, the simulation is performed on 33-bus RDS for twenty independent runs and compared with recently developed dragonfly algorithm (DA) and whale optimization algorithm (WOA). Simulation results demonstrate the effectiveness and stability of GWO algorithm.

关键词： active power filler dragonfly algorithm grey wolf optimizer total harmonic distortion whale optimization algorithm

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