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32nd IEEE International Conference on Advanced Information Networking and Applications (AINA)

作者： Khan, Nasir Javaid, Nadeem Khan, Muhammad Subhani, Ahmed Mateen, Abdul Iqbal, Arshad COMSATS Inst Informat Technol Islamabad 44000 Pakistan Bahauddin Zakariya Univ Dept Informat Technol Multan Pakistan

ISBN: (纸本)9781538621950

Since the development of Smart Grid (SG), Home Energy Management (HEM) systems are emerged widely into it and consumers have an opportunity to schedule their smart appliances efficiently in smart homes. In this research, meta-heuristic techniques harmony search algorithm (HSA), Pigeon Inspired Optimization (PIO) and our proposed harmony Pigeon Inspired Optimization (HPIO) are adopted to efficiently schedule smart appliances in smart home. The aim of using the above proposed techniques is to reduce Electricity Cost (EC) and Peak-to-Average Ratio (PAR). HEM is proposed to further evaluate the performance of evaluated techniques. In this work, single home and multiple homes which consist of 10,30 and 50 homes are considered equipped with multiple smart appliances. These appliances are divided into three sets, which are thermostatically and non-thermostatically controllable, and non-controllable appliances under Time-of Use (ToU) pricing scheme. Simulations are carried out on these parameters and results shows that proposed technique HPIO performed better than HSA and PIO in terms of minimizing waiting time and PAR. We have considered User Comfort (UC) in terms of waiting time.

关键词： smart grid demand response harmony search algorithm peak-to-average ratio user comfort

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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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Improved k-means clustering with Harmonic-Bee algorithms 4

Improved k-means clustering with Harmonic-Bee algorithms

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4th World Congress on Information and Communication Technologies (WICT)

作者： Bonab, Mohammad Babrdel Hashim, Siti Z. Mohd Univ Teknol Malaysia Fac Comp Johor Baharu Malaysia

ISBN: (纸本)9781479981144

Data clustering is one of widely used methods for data mining. The k-means approach is one of the simplest unsupervised learning algorithms that solve the well-known clustering problem. But some hindrances such as the sensitivity to initial values and cluster centers or the risk of trapping in local optimal reduce its best performance. The purpose of kmeans method is minimizing the dissimilarity of observations, from cluster centers. In this paper, a new solution method inspired by harmony search combined with bee algorithm is introduced to improve performance k-means clustering. In this study, harmony and clustering structures are combined to produce harmony clustering. To avoid initial random selection, seed cluster center is considered in primary population as well as bee algorithm has been employed to increase the efficiency of algorithm. The proposed methods have been tested on standard benchmark data sets and also compared to other methods in the literature;it is noted that results show a promising performance leading to better efficiency and capability of the proposed solution.

关键词： harmony search algorithm bee algorithm k-means algorithm data clustering

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Design and Analysis of Optimized Hybrid Active Power Filter for Electric Arc Furnace Load 1st

Design and Analysis of Optimized Hybrid Active Power Filter ...

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1st International Conference on Advanced Computational and Communication Paradigms (ICACCP)

作者： Jhapte, Rajkumar Patel, R. N. Neema, D. D. SSGI Shri Shankaracharya Tech Campus Dept EEE Bhilai Chhattisgarh India Yugantar Inst Technol & Management Dept EEE Rajnandgaon Chhattisgarh India

ISBN: (纸本)9789811082405;9789811082399

Nowadays, nonlinear loads are being proved as a responsible factor for increase in harmonics and lead to current and voltage disturbances, thus declining the potential of the power system. In this paper, the harmonic minimization is carried out by the comparison of the performance of optimization techniques, viz., Genetic algorithm (GA), Particle Swarm Optimization (PSO), and harmony search algorithm (HSA) for tuning the parameters of PI controllers in the implementation on shunt hybrid filter. The modeling approach involves the design of Shunt Hybrid Active Power Filter (SHAPF) using different optimization techniques. The proposed work focuses on using a controlled strategy for extracting the voltage and current harmonics from arc furnace load using hybrid active power filters, and has been implemented using MATLAB platform. The proposed techniques give the THD content which is minimum using HSA as compared to the GA and PSO optimized PI controllers. Thus, the implementation of the proposed work leads to an improvement in the overall performance of the system. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Controller Electric arc furnace load Fast Fourier transform Genetic algorithm harmony search algorithm Hybrid active power filters Optimization technique Particle swarm optimization Power quality Total harmonic distortion

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A Novel Hybrid Penguins search Optimization algorithm to Solve Travelling Salesman Problem 3

A Novel Hybrid Penguins Search Optimization Algorithm to Sol...

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3rd IEEE World Conference on Complex Systems (WCCS)

作者： Mzili, Ilyass Bouzidi, Morad Riffi, Mohammed Essaid Chouaib Doukkali Univ Dept Comp Sci Fac Sci El Jadida Morocco

ISBN: (纸本)9781467396691

Metaheuristics form a family of optimization algorithms for solving combinatorial optimization problems by applying the research procedures to quickly find a good approximation of the best solution. In this paper we proposed a new metaheuristic novel hybrid penguins search optimization algorithm (NPeSOA) which is based on the combination of penguins search optimization algorithm (PeSOA) and harmony search algorithm (HS) to solve the Travelling Salesman Problem. The search for harmony was added to improve the research technique of PeSOA method. The results of this experience are tested by the instances of TSPLib, and compared with the methods of PeSOA and HS to show the efficiency of NPeSOA.

关键词： Metaheuristics combinatorial optimization harmony search algorithm penguins search optimization algorithm novel hybrid penguins search optimization algorithm travelling salesman problem

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Self-Stunding Up of Humanoid Robot Using a New Intelligent algorithm 8

Self-Stunding Up of Humanoid Robot Using a New Intelligent A...

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8th International Conference on Modelling, Identification and Control (ICMIC)

作者： Lachouri, Farid Khelifi, Abdeldjallil Tighzert, Lyes Aguercif, Thafsouth Mendil, Boubekeur Univ Bejaia Fac Technol Dept Genie Elect Bejaia 06000 Algeria Univ Bejaia Fac Technol LTII Bejaia 06000 Algeria

ISBN: (纸本)9780956715777

this paper introduces a new compact intelligent algorithm for global optimization problems. The proposed algorithm is inspired from music improvisation. It is a variant of harmony search algorithm. It is called the compact harmony search algorithm (c SA). It uses a compact representation to store the harmonies in the memory. The proposed intelligent algorithm is compared to the standard version of harmony search algorithm and the results shown that it is very efficient in terms of convergence uality, accuracy, stability and time processing. e give also an application of the algorithm for the realization of self-standing-up of the humanoid robot hydroid.

关键词： compact representation optimization harmony search algorithm hmanoid robot self-standing

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Robust counterpart mathematical models for balancing, sequencing, and assignment of robotic U-shaped assembly lines with considering failures and setup times

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OPsearch 2023年第1期60卷 87-124页

作者： Samouei, Parvaneh Sobhishoja, Mahsa Bu Ali Sina Univ Fac Engn Dept Ind Engn Hamadan Hamadan Iran

In recent years, robots have been widely used in assembly systems called robotic assembly lines, where a set of tasks have to be assigned to stations, and each station needs to select one of the different robots to process the assigned tasks. Our focus is on U-shaped layouts because they are widely employed in many industries due to their efficiency and flexibility compared to straight assembly lines. These lines offer more choices to group operations. A worker can be assigned to multiple stations at the entrance and the exit sides. Moreover, it has been shown experimentally that labor productivity can increase significantly in U-shaped lines. However, in many realistic situations, robots may be unavailable during the scheduling horizon for different reasons, such as breakdowns. This research deals with line balancing under uncertainty. It presents robust optimization models for balancing, sequencing, and robot assignment of U-shaped assembly lines with considering sequencing-dependent setup times, failure robots, and preventive maintenance. The nature of this problem is NP-hard with two objective functions;a multi-objective harmony search is suggested to solve it. The parameters of the proposed algorithm were analyzed using the Taguchi method, and their results were compared with the non-dominated sorting genetic algorithm-II (NSGA-II).

关键词： Metaheuristics Robotic U-shaped mixed-model assembly line harmony search algorithm NSGA-II Preventive maintenance Robust optimization Sequence-dependent setup time

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An Application of Hybrid Nature inspired computational technique to detect faulty element in array antenna 12

An Application of Hybrid Nature inspired computational techn...

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12th INTERNATIONAL BHURBAN CONFERENCE ON APPLIED SCIENCES & TECHNOLOGY (IBCAST)

作者： Khan, Shafqat Ullah Qureshi, Ijaz Mansoor Zaman, Fawad Shoaib, Bilal Ashraf, Kabir ISRA Univ Sch Engn & Appl Sci Islamabad Pakistan Air Univ Islamabad Pakistan COMSATS Inst Informat Technol Islamabad Pakistan Int Islamic Univ Islamabad Pakistan CESAT Islamabad Islamabad Pakistan

ISBN: (纸本)9781479963690

Detection of faulty antenna element in arrays is one of the hot area of research in the field of adaptive beamforming which has direct applications in radar, sonar, mobile communication etc. Due to element failure, the radiation pattern of array is damaged in terms of sidelobes levels, nulls depth and displacement of nulls from their original positions. In order, to correct the faulty pattern, first it is important to precisely detect the respective faulty antenna element. In this work, we introduce hybrid nature inspire technique based on harmony search and firefly algorithm (HS-FA) to detect the position of faulty element in arrays. The HS-FA has shown fairly good accuracy and fast convergence as compared to HS and FA alone. The performance criterion is based on cost function (fitness function) which defines an error between the degraded and estimated power patterns. The simulation results are carried out for Dolph Chebyshev array which consists of 30 elements.

关键词： firefly algorithm harmony search algorithm fault detection

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Comparative Analog Circuit Design Automation Based on Multi-Objective Evolutionary algorithms: an Application on CMOS Opamp 38

Comparative Analog Circuit Design Automation Based on Multi-...

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38th International Conference on Telecommunications and Signal Processing (TSP)

作者： Canturk, Ismail Kahraman, Nihan Yildiz Tech Univ Istanbul Turkey

ISBN: (纸本)9781479984985

Automation of analog integrated circuit (IC) design process is very important because of the optimization contradictions. In this study, benefits of multi-objective evolutionary algorithms are presented on two stage operational amplifier design using harmony search algorithm (HSA) and Non-dominated Sorting Genetic algorithm (NSGA-II). HSA is a new kind of multi-objective evolutionary algorithm which was inspired from the musicians those are looking for the best combination of musical sounds of different instruments that produces most pleasing sound. NSGA-II is an advanced version of genetic algorithm. It combines both current parents and their child population to select new parents. These kinds of design automation tools are required for analog circuit design because there are several contradictions in the design. In this work, transistor sizes which effects all constraints indirectly were automatically synthesized by HSA an NSGA-II.

关键词： Analog circuit automation computer-aided design harmony search algorithm non-dominated sorting genetic algorithm

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Chebyshev polynomial functions based locally recurrent neuro-fuzzy information system for prediction of financial and energy market data

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Journal of Finance and Data Science 2016年第3期2卷 202-223页

作者： Parida, A.K. Bisoi, R. Dash, P.K. Orissa Engineering College Bhubaneswar India Multidisciplinary Research Cell Siksha ‘O’ Anusandhan University Bhubaneswar India

In this paper Chebyshev polynomial functions based locally recurrent neuro-fuzzy information system is presented for the prediction and analysis of financial and electrical energy market data. The normally used TSK-type feedforward fuzzy neural network is unable to take the full advantage of the use of the linear fuzzy rule base in accurate input–output mapping and hence the consequent part of the rule base is made nonlinear using polynomial or arithmetic basis functions. Further the Chebyshev polynomial functions provide an expanded nonlinear transformation to the input space thereby increasing its dimension for capturing the nonlinearities and chaotic variations in financial or energy market data streams. Also the locally recurrent neuro-fuzzy information system (LRNFIS) includes feedback loops both at the firing strength layer and the output layer to allow signal flow both in forward and backward directions, thereby making the LRNFIS mimic a dynamic system that provides fast convergence and accuracy in predicting time series fluctuations. Instead of using forward and backward least mean square (FBLMS) learning algorithm, an improved Firefly-harmony search (IFFHS) learning algorithm is used to estimate the parameters of the consequent part and feedback loop parameters for better stability and convergence. Several real world financial and energy market time series databases are used for performance validation of the proposed LRNFIS model. © 2016 China Science Publishing & Media Ltd.

关键词： Chebyshev polynomials Currency exchange rate prediction Electricity price forecasting Firefly optimization harmony search algorithm Locally recurrent neuro-fuzzy network Stock price prediction TSK fuzzy rules

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