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8th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM)

作者： Parsapoor, Mahboobeh Bilstrup, Urban Halmstad Univ Sch Informat Sci Comp & Elect Engn Halmstad Sweden

ISBN: (纸本)9781612846835;9781612846828

In this paper a novel optimization method called imperialist competitive algorithm (ICA) is applied to solve the channel assignment problem in a mobile ad hoc network. First the imperialist competitive algorithm (ICA) is described, which has been proposed as an evolutionary optimization method, and after that it is explained how it can seek a near optimal solution for the channel allocation problem in a cognitive mobile ad hoc radio network. The simulation results are compared with the results that were obtained by applying island genetic algorithm.

关键词： cognitive radio networks dynamic spectrum access imperialist competitive algorithm interference power

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Prediction of hydrate formation temperature based on an improved empirical correlation by imperialist competitive algorithm

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PETROLEUM SCIENCE AND TECHNOLOGY 2016年第2期34卷 162-169页

作者： Amin, Javad Sayyad Nejad, Samira Keshavarz Babaee Veiskarami, Mehdi Bahadori, Alireza Univ Guilan Dept Chem Engn Rasht Iran Univ Guilan Dept Civil Engn Rasht Iran Shiraz Univ Sch Engn 1 Dept Civil & Environm Engn Shiraz Iran So Cross Univ Sch Environm Sci & Engn Lismore NSW 2480 Australia

Formation of gas hydrates is an important problem in production and transmission of natural gases. Hence, it is a particular interest and also vital to estimate the hydrate formation conditions. To do so, the Katz gas gravity method can be used as one of the simplest techniques. Numerous correlations have been presented so far, among which one of the most popular one with very good accuracy is the so called Ghiasi model. In this study, the imperialist competitive algorithm is applied to improve the Ghiasi correlation by using the Katz data. Error analysis of the results demonstrated that the improved equation had the highest precision in comparison with the Ghiasi correlation and also the other models reported by researchers.

关键词： Gas hydrates hydrate formation temperature Katz gas gravity chart imperialist competitive algorithm

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Minimising earliness and tardiness penalties in single machine scheduling against common due date using imperialist competitive algorithm

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2013年第16期51卷 4797-4804页

作者： Yousefi, Milad Yusuff, Rosnah Mohd Univ Putra Malaysia Dept Mech & Mfg Engn Serdang 43400 Malaysia

In this paper a novel evolutionary-based approach is utilised for efficiently solving the NP-hard problem of scheduling numerous common-due-date jobs on a single machine. Minimising the sum of earliness and tardiness penalties for all jobs is considered as the target function. The performance of the proposed approach is examined through a computational comparative study with 280 benchmark problems with up to 1000 jobs where the numerical results indicate that it can produce better' solutions in less computational time when compared to benchmark results and the methods available in the literature, namely genetic algorithm (GA), Tabu search (TS) and differential evolution (DE).

关键词： scheduling single machine optimisation imperialist competitive algorithm benchmark earliness tardiness

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Ground vibration prediction in quarry blasting through an artificial neural network optimized by imperialist competitive algorithm

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BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT 2015年第3期74卷 873-886页

作者： Hajihassani, Mohsen Armaghani, Danial Jahed Marto, Aminaton Mohamad, Edy Tonnizam Univ Teknol Malaysia Construct Res Alliance Utm Skudai 81310 Johor Malaysia Univ Teknol Malaysia Dept Geotech & Transportat Fac Civil Engn Utm Skudai 81310 Johor Malaysia

This paper presents a new hybrid artificial neural network (ANN) optimized by imperialist competitive algorithm (ICA) to predict peak particle velocity (PPV) resulting from quarry blasting. For this purpose, 95 blasting works were precisely monitored in a granite quarry site in Malaysia and PPV values were accurately recorded in each operation. Furthermore, the most influential parameters on PPV were measured and used to train the ICA-ANN model. Considering the measured data from the granite quarry site, a new empirical equation was developed to predict PPV. For comparison, a pre-developed ANN model was developed for PPV prediction. The results demonstrated that the proposed ICA-ANN model is able to predict blasting-induced PPV better than other presented techniques.

关键词： Blast safety area Ground vibration Peak particle velocity Artificial neural network imperialist competitive algorithm

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A new design approach for shell-and-tube heat exchangers using imperialist competitive algorithm (ICA) from economic point of view

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ENERGY CONVERSION AND MANAGEMENT 2013年 67卷 66-74页

作者： Hadidi, Amin Hadidi, Mojtaba Nazari, Ali Islamic Azad Univ Dept Mech Engn Ahar Branch Ahar Iran

Cost minimization of shell-and-tube heat exchangers is a key objective. Traditional design approaches besides being time consuming, do not guarantee the reach of an economically optimal solution. So, in this research, a new shell and tube heat exchanger optimization design approach is developed based on imperialist competitive algorithm (ICA). The ICA algorithm has some good features in reaching to the global minimum in comparison to other evolutionary algorithms. In present study, ICA technique has been applied to minimize the total cost of the equipment including capital investment and the sum of discounted annual energy expenditures related to pumping of shell and tube heat exchanger by varying various design variables such as tube length, tube outer diameter, pitch size and baffle spacing. Based on proposed method, a full computer code was developed for optimal design of shell and tube heat exchangers and different test cases are solved by it to demonstrate the effectiveness and accuracy of the proposed algorithm. Finally the results are compared to those obtained by literature approaches. The obtained results indicate that the ICA algorithm can be successfully applied for optimal design of shell and tube heat exchangers with higher accuracy in less computational time. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Shell-and-tube heat exchanger Optimal design Economic optimization imperialist competitive algorithm

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Bare-bones imperialist competitive algorithm for a compensatory neural fuzzy controller

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NEUROCOMPUTING 2016年第Part3期173卷 1519-1528页

作者： Chen, Cheng-Hung Chen, Wen-Hsien Natl Formosa Univ Dept Elect Engn Huwei Township 632 Yunlin Taiwan

This study proposes a bare-bones imperialist competitive algorithm (BBICA) for a compensatory neural fuzzy controller in order to solve prediction problems and nonlinear control system problems. In the proposed BBICA, the population is divided into two types: imperialists and colonies. The purpose is that the cultures of colonies and societies can be similar to their empires. Moving colonies toward their relevant imperialist refers the assimilation policy. This study focuses on improving and exploring the process of assimilation. In the assimilation policy, there are two main control parameters for adjusting the direction of motion of colonies, i.e., location and angle. This study proposes the BBICA in order to reduce the use of the control parameters. Therefore, the proposed BBICA adopts a Gaussian distribution to improve the assimilation policy and the exploration ability of the global solution. Finally, the experimental results show that the proposed BBICA better approximates the global optimal solution and that it has faster convergence compared with other methods. (C) 2015 Elsevier B.V. All rights reserved.

关键词： imperialist competitive algorithm Compensatory neural fuzzy controller Function approximation Prediction of a chaotic time series Prediction of a time series Control of backing up the truck

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A hybrid intelligent model combining ANN and imperialist competitive algorithm for prediction of corrosion rate in 3C steel under seawater environment

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NEURAL COMPUTING & APPLICATIONS 2017年第11期28卷 3455-3464页

作者： Shirazi, Amin Zadeh Mohammadi, Zahra NIGC Khorasan Razavi Gas Co Dept Informat & Commun Technol ICT Mashhad Iran Imam Reza Int Univ Dept Comp Engn Mashhad Iran

There are species of carbon steel in the industry suffering from corrosion phenomena under seawater environment. In this paper, for purposes of the prediction of 3C steel corrosion rate, the proposed methodology here adopts a hybrid model based on neural network (NN) and imperialist competitive algorithm (ICA). Additionally, to validate the suggested method, we have managed to apply a procedure, namely leaving-one-out cross-validation (LOOCV). Thus, the model in this paper is abbreviated as NN-ICA_LOOCV. In the case study, the model is implemented on 46 experimental samples. This dataset is included within five parameters, namely temperature, dissolved oxygen, salinity, PH value and oxidation-reduction potential as inputs and corrosion rate(s) as an output parameter. The dataset was divided into two parts: one for training and the other for testing with 42 and 4 data number, respectively. For an evaluation purpose, the performance of NN-ICA_LOOCV is compared with other models on the basis of indicators such as the coefficient of determination (R-2), root-mean-square error (RMSE) and mean absolute error (MAE). The model was successfully tested, yielding a prediction of corrosion rate with a RMSE of around 0.01, MAE of 0.011 and a correlation factor of 0.99 to the test data. The results demonstrate that the carefully designed hybrid model further succeeded to denote lower modeling error and higher accuracy. Hence, this model is an applicable and reliable offer to engineers in order to online and safe prediction of corrosion rate in 3C steel under seawater environment.

关键词： Soft computing Neural networks Prediction Corrosion rate Seawater imperialist competitive algorithm

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Group scheduling in flexible flow shops: a hybridised approach of imperialist competitive algorithm and electromagnetic-like mechanism

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2011年第16期49卷 4965-4977页

作者： Karimi, N. Zandieh, M. Najafi, A. A. Shahid Beheshti Univ Management & Accounting Fac Dept Ind Management GC Tehran Iran Qazvin Islamic Azad Univ Fac Ind & Mech Engn Qazvin Iran KN Toosi Univ Technol Fac Ind Engn Tehran Iran

This paper applied a novel evolutionary algorithm, imperialist competitive algorithm (ICA), for a group scheduling problem in a hybrid flexible flow shop with sequence-dependent setup times by minimising maximum completion time. This algorithm simulates a social-economical procedure, imperialistic competition. Initial population is generated randomly and evolution is carried out during the algorithm. Firstly individuals, countries, are divided into two categories: imperialists and colonies. imperialist competition will occur among these empires. This competition will increase some empires authority by ruining a weak empire and dividing its colonies among others. Electromagnetic-like mechanism concepts are employed here to model the influence of the imperialist on their colonies. The algorithm will continue until one imperialist exists and possesses all countries. In order to prevent carrying out extensive experiments to find optimum parameters of the algorithm, we apply the Taguchi approach. The computational results are compared with the outstanding benchmark on the flow shop scheduling problem, random key genetic algorithms (RKGA), and it shows superiority of the ICA.

关键词： flexible flow shop group scheduling imperialist competitive algorithm electromagnetic-like mechanism Taguchi method

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Optimum design of a line-start permanent-magnet motor with slotted solid rotor using neural network and imperialist competitive algorithm

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IET ELECTRIC POWER APPLICATIONS 2017年第1期11卷 1-8页

作者： Azari, Milad Niaz Mirsalim, Mojtaba Pahnehkolaei, Seyed Mehdi Abedi Mohammadi, Sajjad Univ Sci & Technol Mazandaran Dept Elect Engn Behshahr Iran Amirkabir Univ Technol Dept Elect Engn Tehran Iran St Marys Univ Dept Elect Engn San Antonio TX 78228 USA Islamic Azad Univ Sari Branch Dept Elect Engn Sari Iran

Slotted solid-rotor line-start permanent-magnet motors have good synchronisation capability for high load torques and moment of inertia. This study presents the impacts of rotor-slot parameters such as the slot depth and width to obtain better synchronisation capability. Therefore, the starting torque and the torque near synchronisation speed are considered. For high synchronisation capability these torques should have higher values. To obtain optimum parameters, the artificial neural network and the imperialist competitive algorithm are used. The results obtained show that the values of parameters are very close to the outcomes of the sensitivity analysis. Finally, a four-pole, 1500 rpm, 1050 W, three-phase line-start synchronous motor with an optimised slotted solid rotor is prototyped to confirm the validity of the results.

关键词： rotors permanent magnet motors neural nets synchronisation synchronous motors power engineering computing optimum design line-start permanent-magnet motor slotted solid rotor neural network imperialist competitive algorithm slotted solid-rotor line-start permanent-magnet motors synchronisation capability rotor-slot parameters synchronisation capability torque near synchronisation speed artificial neural network three-phase line-start synchronous motor power 1050 W

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An imperialist competitive algorithm for optimal design of plate-fin heat exchangers

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INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER 2012年第11-12期55卷 3178-3185页

作者： Yousefi, M. Darus, A. N. Mohammadi, H. Univ Teknol Malaysia Fac Mech Engn Dept Thermofluids Skudai 81310 Johor Malaysia Univ Teknol Malaysia Fac Comp Sci Skudai 81310 Johor Malaysia

This paper presents the application of imperialist competitive algorithm (ICA) for optimization of a crossflow plate fin heat exchanger. Minimization of total weight and total annual cost are considered as objectives. Seven design parameters, namely, heat exchanger length at hot and cold sides, fin height, fin frequency, fin thickness, fin-strip length and number of hot side layers are selected as optimization variables. A case study from literature is presented to show the effectiveness of the proposed algorithm. The numerical results reveal that ICA can find optimum configuration with higher accuracy in less computational time when compared to conventional genetic algorithm (GA). (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Plate-fin heat exchanger imperialist competitive algorithm Genetic algorithm Constrained optimization

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