This article addressed two new generation meta-heuristic algorithms that are introduced to the literature recently. These algorithms, proved their performance by benchmark standard test functions, are implemented to s...
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This article addressed two new generation meta-heuristic algorithms that are introduced to the literature recently. These algorithms, proved their performance by benchmark standard test functions, are implemented to solve clustering problems. One of these algorithms called Ions Motion optimization and it is established from the motions of ions in nature. The other algorithm is Weighted Superposition Attraction and it is predicated on two fundamental principles, which are "attracted movements of agents" and "superposition". Both of the algorithms are applied to different benchmark data sets consisted of continuous, categorical and mixed variables, and their performances are compared to particleswarmoptimization and Artificial Bee Colony algorithms. To eliminate the infeasible solutions, Deb's rule is integrated into the algorithms. The comparison results indicated that both of the algorithms, Ions Motion optimization and Weighted Superposition Attraction, are competitive solution approaches for clustering problems. (C) 2017 Elsevier B.V. All rights reserved.
This paper discuss virtual power plant (VPP) and Microgrid controller for energy management system (EMS) based on optimization techniques by using two optimization techniques namely Backtracking search algorithm (BSA)...
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This paper discuss virtual power plant (VPP) and Microgrid controller for energy management system (EMS) based on optimization techniques by using two optimization techniques namely Backtracking search algorithm (BSA) and particle swarm optimization algorithm (PSO). The research proposes use of multi Microgrid in the distribution networks to aggregate the power form distribution generation and form it into single Microgrid and let these Microgrid deal directly with the central organizer called virtual power plant. VPP duties are price forecast, demand forecast, weather forecast, production forecast, shedding loads, make intelligent decision and for aggregate & optimizes the data. This huge system has been tested and simulated by using Matlab simulink. These paper shows optimizations of two methods were really significant in the results. But BSA is better than PSO to search for better parameters which could make more power saving as in the results and the discussion.
Considered the cooperation of the container truck and quayside container crane in the container terminal, this paper constructs the model of the quay cranes operation and trucks scheduling problem in the container ter...
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Considered the cooperation of the container truck and quayside container crane in the container terminal, this paper constructs the model of the quay cranes operation and trucks scheduling problem in the container terminal. And the hybrid intelligence swarmalgorithm combined the particle swarm optimization algorithm(PSO) with artificial fish swarmalgorithm (AFSA) was proposed. The hybrid algorithm (PSO-AFSA) adopt the particle swarm optimization algorithm to produce diverse original paths, optimization of the choice nodes set of the problem, use AFSA's preying and chasing behavior improved the ability of PSO to avoid being premature. The proposed algorithm has more effectiveness, quick convergence and feasibility in solving the problem. The results of stimulation show that the scheduling operation efficiency of container terminal is improved and optimized.
Experimental studies confirm that the obtained electrical power by a conventional photovoltaic PV system is progressively degraded when the temperature of its cells is increased. The water-cooled photovoltaic thermal ...
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Experimental studies confirm that the obtained electrical power by a conventional photovoltaic PV system is progressively degraded when the temperature of its cells is increased. The water-cooled photovoltaic thermal PVT system is therefore proposed to avoid the voltage drop at high temperature. The use of single diode PV/PVT models in simulation software becomes indispensable to analyze its performances where several climatic conditions such as environmental temperature and solar radiation variations should be considered. An optimal set of PV/PVT model parameters are determined through experimental data using two evolutionary computation algorithms;genetic algorithm and particle swarm optimization algorithm. Furthermore, the robustness of the given PV/PVT model should be analyzed. The predicted electrical properties by the proposed PVT model are compared with those given by the conventional PV model at its operating cell conditions and also at several rigid atmospheric conditions.
This study proposes an evolutionary-based clustering algorithm based on a hybrid of genetic algorithm (GA) and particle swarm optimization algorithm (PSOA) for order clustering in order to reduce surface mount technol...
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This study proposes an evolutionary-based clustering algorithm based on a hybrid of genetic algorithm (GA) and particle swarm optimization algorithm (PSOA) for order clustering in order to reduce surface mount technology (SMT) setup time. Simulational results via Iris, Glass, Vowel and Wine benchmark data sets indicate that the proposed evolutionary-based clustering algorithm is more accurate than the GA-based and PSOA-based clustering algorithms. In addition, the model evaluation results which use order information provided by an international industrial personal computer (PC) manufacturer show that the proposed algorithm is also superior to GA-based and PSOA-based clustering algorithms. Through order clustering, scheduling orders that belong to the same cluster together can reduce production time as well as machine idle time. (C) 2010 Elsevier B.V. All rights reserved.
Telecommunication package is a product produced by telecom operator to satisfy different consumer groups. Telecom operator should not only consider the users' acceptability, but also enable to maximize profits. Ho...
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ISBN:
(纸本)9783319274003;9783319273990
Telecommunication package is a product produced by telecom operator to satisfy different consumer groups. Telecom operator should not only consider the users' acceptability, but also enable to maximize profits. However, how to balance the relationship of both and designing a package are very important tasks and complicated problems. At present, design of telecom package is affected greatly by designer's subjective experience which is blind. In this paper, a new idea of automatic discovery and recommendation for telecom package is proposed. This idea is combined user's acceptance with operator's profit. The package model and customer model are set up based on consumption of customers. particleswarmoptimization is used for discovering an inverse package. Meanwhile, the potential customers of the targets are selected by calculating proportion of package attribute usage. Experimental results show that the proposed method has favorable performance.
In this study, it is aimed to tracking a satellite on mobile vehicles for receiving the broadcasting signal of the satellite. Satellite tracking is used in many areas on mobile platforms. Too many problems come with t...
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ISBN:
(纸本)9781509048281
In this study, it is aimed to tracking a satellite on mobile vehicles for receiving the broadcasting signal of the satellite. Satellite tracking is used in many areas on mobile platforms. Too many problems come with the mobility. A robust tracking algorithm is need for overcome such problems. The robust satellite tracking case is researched and test software is developed for Android based platforms. Satellite tracking can be done with a receiver antenna by adjusting the positions according to the movements of the vehicle. Therefore Kalman Filter and particle swarm optimization algorithm are compared in the use of satellite tracking process. An Android based application was developed to accomplish this and tests were performed using an android - based device on a mobile vehicle. Test data were collected through application from the sensors of the android device. Orientation and location data of the mobile vehicle are collected from the device sensors and they are used in computation of the azimuth and elevation angles of receiver antenna. Two well-known algorithms were implemented and performed on the application for tracking to keep satellite link online. It was systemically investigated the estimation and computational performance of the two algorithm on this subject. The results and test cases were analyzed and discussed. Test cases cover the computation of the azimuth and elevation angles.
Carmine is a widely used food pigment in various food and beverage additives. Excessive consumption of synthetic pigment shall do harm to body seriously. The food is generally associated with a variety of colors. Unde...
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ISBN:
(数字)9781510619784
ISBN:
(纸本)9781510619784
Carmine is a widely used food pigment in various food and beverage additives. Excessive consumption of synthetic pigment shall do harm to body seriously. The food is generally associated with a variety of colors. Under the simulation context of various food pigments' coexistence, we adopted the technology of fluorescence spectroscopy, together with the PSO-SVM algorithm, so that to establish a method for the determination of carmine content in mixed solution. After analyzing the prediction results of PSO-SVM, we collected a bunch of data: the carmine average recovery rate was 100.84%, the root mean square error of prediction (RMSEP) for 1.03e-04, 0.999 for the correlation coefficient between the model output and the real value of the forecast. Compared with the prediction results of reverse transmission, the correlation coefficient of PSO-SVM was 2.7% higher, the average recovery rate for 0.6%, and the root mean square error was nearly one order of magnitude lower. According to the analysis results, it can effectively avoid the interference caused by pigment with the combination of the fluorescence spectrum technique and PSO-SVM, accurately determining the content of carmine in mixed solution with an effect better than that of BP.
A novel method coupling particle swarm optimization algorithm (PSO) and genetic algorithm (GA) was proposed to optimize simultaneously the kernel parameters of support vector machine (SVM) and determine the optimized ...
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A novel method coupling particle swarm optimization algorithm (PSO) and genetic algorithm (GA) was proposed to optimize simultaneously the kernel parameters of support vector machine (SVM) and determine the optimized features subset. By coupling GA with PSO, the particles produced in each generation in PSO algorithm were processed by crossover and mutation of GA, and then the particles could keep diversity to escape from local optima and find the global optima quickly and accurately. In order to evaluate the proposed method, four peptide datasets were employed for the investigation of quantitative structure-activity relationship (QSAR). The structural and physicochemical features of peptides from amino acid sequences were used to represent peptides for QSAR. The correlation coefficients (R) of training set of the four datasets were 1.0000, 0.9508, 1.0000, 0.9995, the R of test set of the four datasets were 0.9922, 0.9687, 0.9022, 0.7404, respectively. The root-mean-square errors (RMSEs) of training set of the four datasets were 0.0000, 0.0986, 0.0000, 0.0203, the RMSEs of test set of the four datasets were 0.2522, 0.2782, 0.9625, 0.2928, respectively. A protein dataset, which consists of 277 proteins, was also employed to evaluate the current method for predicting protein structural class, and the good results of overall success rate were obtained. The results indicated that the proposed method might hold a high potential to become a useful tool in peptide QSAR and protein prediction research. (C) 2010 Elsevier Inc. All rights reserved.
The comprehensive evaluation of electric construction project is one of the main tasks in the early stage of the project. In order to accurately embody the nature, content, and scale of the reserve projects, a quantit...
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The comprehensive evaluation of electric construction project is one of the main tasks in the early stage of the project. In order to accurately embody the nature, content, and scale of the reserve projects, a quantitative evaluation method for reserve projects based on the contribution of power grid is proposed in this paper. An evaluation index system and its quantitative calculation method are established, And the optimal weight of each index is determined by utilizing the combination assigning method and particle swarm optimization algorithm. Then the contribution evaluation model of power grid reserve project is constructed based on the contribution and project investment. The dynamic sorting method for power grid reserve projects is determined by analyzing the coupling relationship and decoupling method in the reserve projects. Finally, the distribution network expansion projects in a certain city are taken as an example, and the results are presented to illustrate the usefulness of proposed method.
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