Search Results - (( simulation optimization based algorithm ) OR ( variable validating a algorithm ))

Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

“…Besides, some real data sets were examined to validate the proposed algorithm. Empirical evidences based on simulated data sets indicated that the proposed modified k-means algorithm is able to recognise the optimum number of clusters for uncorrelated data sets. …”
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A firefly algorithm based hybrid method for structural topology optimization by Gebremedhen, H.S., Woldemichael, D.E., Hashim, F.M.

“…The lower and upper limit of design variables (0 and 1) were used to find initial material distribution to initialize the firefly algorithm based section of the hybrid algorithm. …”
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Imposed weighting factor optimization method for torque ripple reduction of IM fed by indirect matrix converter with predictive control algorithm by Uddin, M., Mekhilef, Saad, Rivera, M., Rodriguez, J.

“…The predictive control algorithm selects the optimum switching state that minimizes a cost function based on optimized weighting factor to actuate the indirect matrix converter. …”
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A new algorithm for normal and large-scale optimization problems: Nomadic People Optimizer by Alsewari, Abdul Rahman Ahmed, Sinan, Q. Salih

“…The algorithm is validated based on 36 unconstrained benchmark functions. …”
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Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio... by Daba, Layth Muwafaq Abdulhussein

“…Unlike the existing optimization algorithm, VL-WIDE features the capability of searching different lengths of solutions to cover the variable number of cloudlets for deployment. …”
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Automatic control of flotation process using computer vision by Saravani, Ali Jahed

“…A froth model correlating the image variables to process variables and a prediction system estimating the metallurgical parameters based on image variables were then developed by using a neural network structure. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Global Particle Swarm Optimization for High Dimension Numerical Functions Analysis by Jamian, J.J., Abdullah, M.N., Mokhlis, Hazlie, Mustafa, M.W., Bakar, Ab Halim Abu

“…To overcome this problem, an efficient Global Particle Swarm Optimization (GPSO) algorithm is proposed in this paper, based on a new updated strategy of the particle position. …”
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An Optimal Scheduling Controller for Virtual Power Plant and Microgrid Integration Using the Binary Backtracking Search Algorithm by Abdolrasol M.G.M., Hannan M.A., Mohamed A., Amiruldin U.A.U., Abidin I.B.Z., Uddin M.N.

Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

“…In order to validate the proposed algorithm, a number of experiments using various datasets were conducted and compared the outcomes with different�state-of-the-art algorithms. …”

Role of optimization algorithms based fuzzy controller in achieving induction motor performance enhancement by Hannan M.A., Ali J.A., Hossain Lipu M.S., Mohamed A., Ker P.J., Indra Mahlia T.M., Mansor M., Hussain A., Muttaqi K.M., Dong Z.Y.

Independent And Dependent Job Scheduling Algorithms Based On Weighting Model For Grid Environment by M. Al-Najjar, Hazem

“…However, the previous algorithms are complicated and needed a lot of computational resources. …”
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Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224) by Mahat, Nor Idayu, Engku Abu Bakar, Engku Muhammad Nazri, Zakaria, Ammar, Mohd Nazir, Mohd Amril Nurman, Misiran, Masnita

“…This study developed an algorithm for statistical classification that enable ones to classify a future data to one of predetermined groups based on the measured data which facing two major threats; (i) multicollinearity among the measured variables and (ii) imbalanced groups. …”
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

“…Moreover, K-Nearest Neighbor (KNN) classifier was used to evaluate the effectiveness of the features identified by the proposed SCSO algorithm. The performance of the proposed SCSO algorithm was compared with six state-of-the-art and recent wrapper-based optimization algorithms using the validation metrics of classification accuracy, optimum feature size, and computational cost in seconds. …”
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A Fuzzy Logic Controller Based on Maximum Power Point Tracking Algorithm for Partially Shaded PV Array-Experimental Validation by Benlahbib, Boualam, Bouarroudj, Noureddine, Mekhilef, Saad, Abdelkrim, Tameur, Lakhdari, Abdelkader, Bouchafaa, Farid

“…An experimental study is conducted using DSPACE 1104 card real-time board under partial shading condition. Simulation and experimental results show that the proposed controller exhibits less settling time and lower overshoot than the commonly used perturb and observe (P&O) algorithm in the transient state and minimum oscillation around the optimal operating point.…”
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Optimizing energy and reserve minimization in a sustainable microgrid with electric vehicle integration: dynamic and adjustable manta ray foraging algorithm by Abed, Adnan Ajam, Suwaed, Mahmood Sh., Al-Rubaye, Ameer H., Awad, Omar I., Mohammed, M.N, Hai, Tao, Kadirgama, Kumaran, Karah Bash, Ali A. H.

“…This paper presents a novel approach for optimizing energy and reserve minimization in a sustainable integrated microgrid with electric vehicles (EVs) by the use of the dynamic and adjustable Manta Ray Foraging (DAMRF) algorithm. …”
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Machine Learning Based Optimal Design of On-Road Charging Lane for Smart Cities Applications by Shanmugam Y., Narayanamoorthi R., Ramachandaramurthy V.K., Bernat P., Shrestha N., Son J., Williamson S.S.

“…The learning algorithms consider variables such as core structure, cross-coupling effect, and coil flux pipe length. …”

Long-term optimal planning for renewable based distributed generators and battery energy storage systems toward enhancement of green energy penetration by ALAhmad A.K., Verayiah R., Shareef H.

“…To solve the optimization planning model, a hybrid optimization algorithm is proposed, combining the non-dominating sorting genetic algorithm (NSGAII) and multi-objective particle swarm optimization (MOPSO). …”

Hybrid ANN and Artificial Cooperative Search Algorithm to Forecast Short-Term Electricity Price in De-Regulated Electricity Market by Pourdaryaei, Alireza, Mokhlis, Hazlie, Illias, Hazlee Azil, Kaboli, S. Hr. Aghay, Ahmad, Shameem, Ang, Swee Peng

“…Therefore, this research proposes a hybrid method for electricity price forecasting via artificial neural network (ANN) and artificial cooperative search algorithm (ACS). …”
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Capacity Planning For Mixed-Load Tester Under Demand And Testing Time Uncertainty by Asih, Hayati Mukti

“…Currently,the company’s issue is low tester utilization of about 71%,well below the target of 96%.The objective of this research is to improve tester utilization while achieving the production target under uncertain demand and testing time and also to determine the break-even point on the testers required.A novel approach of integrating a mathematical model,robust optimization model,genetic algorithm,simulation model and cost–volume –profit analysis was developed.Firstly,a mathematical model of mixed-load tester was formulated.Next,a set of discrete scenarios was proposed to address uncertain demand and testing time.A robust optimization and genetic algorithm model was developed to optimize the number of testers under the described uncertainties.Next,these scenarios were simulated using the Pro Model simulation software to validate the proposed models and to evaluate throughput and tester utilization.Finally,the cost–volume–profit analysis was performed for scenarios that require additional testers at various levels of uncertainties.The results showed that the proposed solution improved tester utilization by 25% compared to the current system.This research has contribution by developing novel hybrid methodology and able to provide useful insights to assist company’s managers to plan and allocate resources according to variations in customers’ demands and testing time.…”
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