Search Results - (( data distribution modified algorithm ) OR ( parameters motivation search algorithm ))

An analysis of the parameter modifications in varieties of harmony search algorithm by Mansor, N. F., Abal Abas, Zuraida, Abdul Rahman, Ahmad Fadzli Nizam, Shibghatullah, Abdul Samad, Safiah , Sidek

“…A Harmony Search (HS) algorithm is a population based-meta-heuristics approach that is superior in solving diversified and large scale optimization problems. …”
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Local search manoeuvres recruitment in the bees algorithm by Muhamad, Zaidi, Mahmuddin, Massudi, Nasrudin, Mohammad Faidzul, Sahran, Shahnorbanun

“…The Bees Algorithm (BA) was created specifically by mimicking the foraging behavior of foraging bees in searching for food sources.During the searching, the original BA ignores the possibilities of the recruits being lost during the flying.The BA algorithm can become closer to the nature foraging behavior of bees by taking account of this phenomenon.This paper proposes an enhanced BA which adds a neighbourhood search parameter which we called as the Local Search Manoeuvres (LSM) recruitment factor.The parameter controls the possibilities of a bee extends its neighbourhood searching area in certain direction.The aim of LSM recruitment is to decrease the number of searching iteration in solving optimization problems that have high dimensions.The experiment results on several benchmark functions show that the BA with LSM performs better compared to the one with basic recruitment.…”
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An analysis of the parameter modifications in varieties of harmony search algorithm by Nur Farraliza, Mansor, Zuraida, Abal Abas, Ahmad Fadzli Nizam, Abdul Rahman

“…A Harmony Search (HS) algorithm is a population based-meta-heuristics approach that is superior in solving diversified and large scale optimization problems. …”
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A hybrid SP-QPSO algorithm with parameter free adaptive penalty method for constrained global optimization problems by Fatemeh, D. B., Loo, C. K., Kanagaraj, G., Ponnambalam, S. G.

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LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, M. N. M., Kahar

“…The importance of optimizing Least Squares Support Vector Machines (LSSVM) embedded control parameters has motivated researchers to search for proficient optimization techniques. …”
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Simultaneous computation of model order and parameter estimation for ARX model based on single swarm and multi swarm simulated Kalman filter by Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Pebrianti, Dwi, Mohd Saberi, Mohamad

“…Agents interact among them to modify and enhance the solution throughout the search process. Simultaneous Model Order and Parameter Estimation (SMOPE) and Simultaneous Model Order and Parameter Estimation based on Multi Swarm (SMOPE-MS) are two techniques of implementing meta-heuristic algorithm to iteratively establish an optimal model order and parameters simultaneously for an unknown system. …”
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Efficient Time-Varying q-Parameter Design for q-Incremental Least Mean Square Algorithm with Noisy Links by Arif, M., Khan, S.S., Qadri, S.S.U., Naseem, I., Moinuddin, M.

“…The quantum calculus provides an extra degree of freedom to search the local and global minima by inducing a q-parameter. …”
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Inverse identification of elastic properties of composite materials using hybrid GA-ACO-PSO algorithm by Tam, Jun Hui, Ong, Zhi Chao, Ismail, Zubaidah, Ang, Bee Chin, Khoo, Shin Yee, Li, Wen L.

“…In the proposed algorithm, the effect of random initialization of GA is subdued by passing the products of GA through the ACO and PSO operators to well organize the exploitative and exploratory search coverage. …”
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Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data by Hamza, Abubakar

“…The present study proposes a simulated annealing algorithm (SA) in estimating the parameters of Weibull distribution with application to modified internal rate of return data (MIRR).The objective is to examine the investment potential of the shari’ah compliance companies of the Malaysia property sector (MPS). …”
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Modifying maximum likelihood test for solving singularity and outlier problems in high dimensional cases by Hafeez, Ahmad

“…However, the performance of the classical location and scatter estimators is usually flawed by singularity and outliers’ problems in high dimensional data sets. The study aimed to modify the existing ML test by incorporating the Cholesky banded regularization methods and thresholding sample covariance matrix to resolve singularity problems and incorporating the L₁-median with Weiszfeld’s algorithm (MLw) covariance matrix to solve outliers’ problem in high dimensional data sets. …”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

“…Genetic Algorithm (GA) is used to search for the best parameter of SVM classification by using combination of random and pre-populated genomes from Pre-Populated Database (PPD). …”

A modified weight optimisation for higher-order neural network in time series prediction by Husaini, Noor Aida

“…Therefore, a modification was made by the additional step of information exchange between the top eggs, which significantly improve the convergence rate. Hence, motivated by the advantages of those Modified Cuckoo Search (MCS), the improvement of the MCS called Modified Cuckoo Search-Markov chain Monté Carlo (MCS-MCMC) learning algorithm is proposed for weight optimisation. …”
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Modified sequential fences for identifying univariate outliers by Wong, Hui Shein

“…Moreover, we proposed a new method with modified algorithm and methodology namely bootstrap sequential fences. …”
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Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee by Chong , Hue Yee

“…In this research work, the motivation is to develop an autonomous learning model based on the hybridization of an adaptive ANN and a metaheuristic algorithm for optimizing ANN parameters so that the network could perform learning and adaptation in a more flexible way and handle condition classification tasks more accurately in industries, such as in power systems. …”
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A Social Based Model For Genetic Algorithms. by AL-Madi, Nagham Azmi, Khader, Ahamad Tajudin

“…Genetic algorithms (GAs), as a general search model, have proved its success in several applications, however, recently, several researchers have argued that they have slow convergence; this slowness is due to the randomness in all their operations. …”
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Improving on the network lifetime of clustered-based wireless sensor network using modified leach algorithm by Zeni, Saltihie

“…Then, the modified LEACH algorithm was proposed where the improvement was done in cluster head selection based on LEACH. …”
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Stochastic And Modified Sequent Peak Algorithm For Reservoir Planning Analysis Considering Performance Indices by Oskoui, Issa Saket

“…In the next stage, the modified Sequent Peak Algorithm (SPA) is employed for the Storage-yield planning analysis of reservoir systems at different demands, reliability and vulnerability performance metrics employing the synthetic streamflow data. …”
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Smart grid: Bio-inspired algorithms energy distributions for data centers by Woo, Yu Hang

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Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment by Kalaf, Kalaf, Bayda Atiya

“…The proposed strategy is dependent on modified Zimmermanns approach for handling all inexact operating costs, data capacities, and demand variables. …”
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A dynamic replication aware load balanced scheduling for data grids in distributed environments of internet of things by Bakhshad, Said, Noor, Rafidah Md, Akhundzada, Adnan, Saba, Tanzila, Ahmedy, Ismail, Haroon, Faisal, Nazir, Babar

“…Grid computing is a powerful distributed and scalable computing infrastructure that deals with massive data-intensive applications. …”
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