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A hybrid optimization-based deep belief neural network for the classification of vegetation area in multi-spectral satellite image

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INTERNATIONAL JOURNAL OF KNOWLEDGE-BASED AND INTELLIGENT ENGINEERING SYSTEMS 2020年第4期24卷 363-379页

作者： Gavade, Anil B. Rajpurohit, Vijay S. KLS Gogte Inst Technol Belagavi 590008 Karnataka India

Over the last few decades, multiple advances have been done for the classification of vegetation area through land cover, and land use. However, classification problem is one of the most complicated and contradicting problems that has received considerable attention. Therefore, to tackle this problem, this paper proposes a new Firefly-harmony search based Deep Belief Neural Network method (FHS-DBN) for the classification of land cover, and land use. The segmentation process is done using Bayesian Fuzzy Clustering,and the feature matrix is developed. The feature matrix is given to the proposed FHS-DBN method that distinguishes the land coverfrom the land use in the multispectral satellite images, for analyzing the vegetation area. The proposed FHS-DBN method is designedby training the DBN using the FHS algorithm, which is developed by the combination of Firefly algorithm (FA) and harmony search (HS) algorithm. The performance of the FHS-DBN model is evaluated using three metrics, such as Accuracy, True Positive Rate (TPR), and False Positive Rate (FPR). From the experimental analysis, it is concludedthat the proposed FHS-DBN model achieves ahigh classification accuracy of 0.9381, 0.9488, 0.9497, and 0.9477 usingIndian Pine, Salinas scene, Pavia Centre and university, and Pavia University scene dataset.

关键词： Classification multi-spectral satellite image firefly algorithm harmony search algorithm DBN vegetation index

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Improved Novel Global harmony search Optimization for Robust Pole Assignment in Descriptor Systems 30

Improved Novel Global Harmony Search Optimization for Robust...

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30th Chinese Control and Decision Conference (CCDC)

作者： Zhai, Junchang Gao, Liqun Bohai Univ Coll Informat Sci & Technol Jinzhou 121013 Peoples R China Northeastern Univ Sch Informat Sci & Engn Shenyang 110819 Peoples R China

ISBN: (纸本)9781538612446

To improve the optimization performance of harmony search algorithm, an improved novel global harmony search (INGHS) algorithm with new improvisation process is proposed in this paper. INGHS algorithm is presented to address robust pole assignment for descriptor system With all the finite poles restrict in an arbitrary specified circular region. The object is converted into a nonlinear optimization problem with constraints for the transient performance request. In terms of the robust circular region stability constraints, the upper hound of the spectral norm for the perturbation or the uncertainty is optimized such that the desired poles of the closed-loop system and the state feedback controller can be optimized simultaneously. To evaluate the performance of the proposed INGHS algorithm, comparison with other harmony search variants algorithm for the problem is carried out. Finally, the simulation results illustrate the effectiveness of the proposed method.

关键词： descriptor system robust pole assignment region stability harmony search algorithm

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Research on Telecom Customer Churn Prediction Method Based on Data Mining 14th

Research on Telecom Customer Churn Prediction Method Based o...

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14th CCF Conference on Computer Supported Cooperative Work and Social Computing

作者： Liang, Xuechun Chen, Shuqi Chen, Chen Zhang, Taoning Nanjing Tech Univ Nanjing Peoples R China

ISBN: (纸本)9789811513770;9789811513763

Aiming at overcoming the shortcomings of common telecommunication customer churn prediction models as single model and poor classification performance, a gradient decision tree integration model (GBDT) prediction model is proposed, and the important parameters are searched by harmonic search algorithm (HS). We built a telecom customer churn prediction model based on HS-GBDT algorithm. This model compares the parameter combinations to be optimized in the GBDT algorithm into the synthesized harmony in the HS algorithm, and seeks the optimal parameter combination of the GBDT model through continuous iteration of the harmony. The experimental results show that the combined model has higher classification accuracy than Logistic regression, support vector machine and random forest, and can provide good decision support for major telecom operators in the process of customer churn management.

关键词： Telecom customer churn prediction harmony search algorithm Gradient Boosting Decision Tree Combined model

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Optimal Distribution for Hydropower Load with Wind-energy 10

Optimal Distribution for Hydropower Load with Wind-energy

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10th International Conference on Applied Energy (ICAE)

作者： Ge, Yeshuai Mo, Li Wang, Yongqiang Huazhong Univ Sci & Technol Shcool Hydropower & Informat Engn Wuhan 430074 Hubei Peoples R China Changjiang River Sci Res Inst Wuhan 430015 Hubei Peoples R China

In this paper, the optimal distribution model of hydropower load is proposed and the operation constraints of wind power and hydropower are taken into consideration. In the process of sending power to the provincial network, the harmonic search algorithm is introduced to optimize the maximum power generation target, and the validity of the model is verified in the case of central China regional power grid. (C) 2019 The Authors. Published by Elsevier Ltd.

关键词： Central China wind power generation hydropower generation hybrid power generation load distribution harmony search algorithm

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An Improved Optimization algorithm Applied in Image Processing

An Improved Optimization Algorithm Applied in Image Processi...

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第32届中国控制与决策会议

作者： Ping Zhang John Douglas Thomson Yining Zhang Physics Department Anshan Normal University Graduate School of Business and Law RMIT University

Aim to improve the default of harmony search（HS） algorithm which is easily trapping into local optima while doing global *** improved optimization algorithm presented in this *** historical iteration information to set up an instructive dataset,then the global search mechanism is combined with a local search *** that,an integer planning study based on distance strategy and the fuzzy constraint processing in spatial division of solution *** proposed model combines with FCM applied in image *** experimental results show that the proposed method can get more accuracy and less CPU operation time versus FCM and s-FCM.

关键词： harmony search algorithm Image Processing FCM Local Optimization

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Locating and Sizing of Series FACTS Devices Using Line Outage Sensitivity Factors and harmony search algorithm

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Energy Procedia 2012年 14卷 1445-1450页

作者： H. Javaheri R. Goldoost-Soloot Department of Electrical Engineering University of Javid P.O.Box: 78615551 Jiroft Iran

This paper proposes the use of series FACTS devices to relieve congestion and enhance the security in restructured power system. harmony search algorithm as a novel heuristic algorithm is employed for optimal locating and sizing of series FACTS devices. In order to reduce the solution space and to pinpoint the lines which are more suitable for FACTS device placement line outage sensitivity factors is employed. Two different objective functions are considered in the optimization problem, the first one is the total congestion cost and the other is total generation cost. To validate the effectiveness of the proposed method and show its efficiency, the simulations are carried out on IEEE 14-bus test system. The results of the proposed method are compared with those obtained by particle swarm optimization and with those obtained by congestion rent contribution method.

关键词： Congestion management Series FACTS devices line outage sensitivity factors harmony search algorithm

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An improved harmony search based energy-efficient routing algorithm for wireless sensor networks

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APPLIED SOFT COMPUTING 2016年 41卷 135-147页

作者： Zeng, Bing Dong, Yan Huazhong Univ Sci & Technol Sch Mech Sci & Engn State Key Lab Digital Mfg Equipment & Technol 1037 Luoyu Rd Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Elect & Informat Engn Dept 1037 Luoyu Rd Wuhan 430074 Peoples R China

Wireless sensor networks (WSNs) is one of the most important technologies in this century. As sensor nodes have limited energy resources, designing energy-efficient routing algorithms for WSNs has become the research focus. And because WSNs routing for maximizing the network lifetime is a NP-hard problem, many researchers try to optimize it with meta-heuristics. However, due to the uncertain variable number and strong constraints of WSNs routing problem, most meta-heuristics are inappropriate in designing routing algorithms for WSNs. This paper proposes an Improved harmony search Based Energy Efficient Routing algorithm (IHSBEER) for WSNs, which is based on harmony search (HS) algorithm (a meta-heuristic). To address the WSNs routing problem with HS algorithm, several key improvements have been put forward: First of all, the encoding of harmony memory has been improved based on the characteristics of routing in WSNs. Secondly, the improvisation of a new harmony has also been improved. We have introduced dynamic adaptation for the parameter HMCR to avoid the prematurity in early generations and strengthen its local search ability in late generations. Meanwhile, the adjustment process of HS algorithm has been discarded to make the proposed routing algorithm containing less parameters. Thirdly, an effective local search strategy is proposed to enhance the local search ability, so as to improve the convergence speed and the accuracy of routing algorithm. In addition, an objective function model that considers both the energy consumption and the length of path is developed. The detailed descriptions and performance test results of the proposed approach are included. The experimental results clearly show the advantages of the proposed routing algorithm for WSNs. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Wireless sensor networks Routing algorithms Energy-efficient Meta-heuristic harmony search algorithm

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Optimized symmetric partial facegraphs for face recognition in adverse conditions

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INFORMATION SCIENCES 2018年 429卷 194-214页

作者： Lahasan, Badr Lutfi, Syaheerah Lebai Venkat, Ibrahim Al-Betar, Mohammed Azmi San-Segundo, Ruben Univ Sains Malaysia Sch Comp Sci George Town 11800 Usm Malaysia Al Balqa Appl Univ Al Huson Univ Coll Dept Informat Technol Salt Jordan Univ Politecn Madrid ETSI Telecomunicac ETSIT Grp Technol Habla Madrid Spain

In this paper, We propose a memetic based framework called Optimized Symmetric Partial Facegraphs (OSPF) to recognize faces prone to adverse conditions such as facial occlusions, expression and illumination variations. Faces are initially segmented into facial components and optimal landmarks are automatically generated by exploiting the bilateral symmetrical property of human faces. The proposed approach combines an improved harmony search algorithm and an intelligent single particle optimizer to take advantage of their global and local search capabilities. Basically, the hybridization version aids to compute the optimal landmarks. These landmarks further serve as the building blocks to intuitively construct the partial facegraphs. The efficiency of the proposed approach has been investigated in addressing the facial occlusion problem when only one exemplar face image per subject is available using comprehensive experimental validations. The proposed approach yields improved recognition rates when compared to recent state-of-the-art techniques. (C) 2017 Elsevier Inc. All rights reserved.

关键词： Face recognition Facial occlusion Symmetric partial facegraphs harmony search algorithm Intelligent single particle optimizer

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Metaheuristic Optimization of Reinforced Concrete Footings

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KSCE JOURNAL OF CIVIL ENGINEERING 2018年第11期22卷 4555-4563页

作者： Nigdeli, Sinan Melih Bekdas, Gebrail Yang, Xin-She Istanbul Univ Dept Civil Engn TR-34320 Istanbul Turkey Middlesex Univ Sch Sci & Technol London England

The primary goal of an engineer is to find the best possible economical design and this goal can be achieved by considering multiple trials. A methodology with fast computing ability must be proposed for the optimum design. Optimum design of Reinforced Concrete (RC) structural members is the one of the complex engineering problems since two different materials which have extremely different prices and behaviors in tension are involved. Structural state limits are considered in the optimum design and differently from the superstructure members, RC footings contain geotechnical limit states. This study proposes a metaheuristic based methodology for the cost optimization of RC footings by employing several classical and newly developed algorithms which are powerful to deal with non-linear optimization problems. The methodology covers the optimization of dimensions of the footing, the orientation of the supported columns and applicable reinforcement design. The employed relatively new metaheuristic algorithms are harmony search (HS), Teaching-Learning Based Optimization algorithm (TLBO) and Flower Pollination algorithm (FPA) are competitive for the optimum design of RC footings.

关键词： reinforced concrete footings optimization metaheuristic algorithms harmony search algorithm teaching-learning based optimization flower pollination algorithm

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A novel bat algorithm based optimum tuning of mass dampers for improving the seismic safety of structures

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ENGINEERING STRUCTURES 2018年第Mar.15期159卷 89-98页

作者： Bekdas, Gebrail Nigdeli, Sinan Melih Yang, Xin-She Istanbul Univ Dept Civil Engn TR-34320 Istanbul Turkey Middlesex Univ Design Engn & Math London England

Metaheuristic algorithms are effective for optimization with diverse applications in engineering. The optimum tuning of tuned mass dampers is very important for seismic structures excited by random vibrations, and optimization techniques have been used to obtain the best performance for optimally tuned mass dampers. In this study, a novel optimization approach employing the bat algorithm with several modifications for the tuned mass damper optimization problem is presented. In the proposed method, the design variables such as the mass, period and damping ratio of tuned mass damper are optimized and different earthquake records are considered during the optimization process. The method is then applied to a ten-story civil structure and the results are then compared with the analytical methods and other methods such as genetic algorithms, particle swarm optimization, and harmony search. The comparison shows that the proposed method is more effective than other compared methods. Additionally, the robustness of the optimum results was evaluated. The proposed approach for optimizating tuned mass dampers via the bat algorithm is a feasible and efficient approach.

关键词： Tuned Mass Damper Optimization Metaheuristic algorithms Bat algorithm harmony search algorithm

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