Search Results - (( evolution optimization bat algorithm ) OR ( variable simulation modified algorithm ))

Multi-Swarm bat algorithm by Taha A.M., Chen S.-D., Mustapha A.

“…In this study a new Bat Algorithm (BA) based on multi-swarm technique called the Multi-Swarm Bat Algorithm (MSBA) is proposed to address the problem of premature convergence phenomenon. …”

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

“…In order to obtain the optimum number of clusters and at the same time could deal with correlated variables in huge data, modified k-means algorithm was proposed. …”
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Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff by Mohd Yusoff, Nurulanis

“…Basically, the QEEA is based on the Time Domain (TD) and Frequency Domain (FD) scheduling where it is dependent on the QoS requirements to allocate resources. The proposed algorithm is compared against other scheduling algorithms, namely, the Channel and QoS Aware (CQA), Priority Set Scheduler (PSS), Proportional Fair (PF), Maximum Throughput (MT) and Blind Average Throughput (BAT). …”
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Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data by Baba, Ishaq Abdullahi

“…The performance of the proposed method is illustrated using simulation study and on glass vessel data with 1920 variables, cardiomyopathy microarray data with 6319 variables, and octane data with 226 dimensions. …”
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Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment by Kalaf, Kalaf, Bayda Atiya

“…During the course of the present work, two fuzzy methods (modified Zimmermanns approach and modified angelovs approach ) and fourmeta-heuristics and hybrid meta heuristics including; simulated annealing (SA), modified simulated annealing (MSA), hybrid modified simulated annealing and simplex downhill (MSASD), hybrid modified simulated annealing and modified particle swarm optimization (MSAPSO) were proposed. …”
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An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion by Haque, Ariful

“…Many researchers suggested the adoption of Modified Condition / Decision Coverage (MC/DC) criterion as a solution to the problem particularly when the inputs involve Boolean variables. …”
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Simulation Of Token Bucket Algorithm For Network Traffic Performance by Yusof, Robiah, Mat Nawi, Nor Afifah

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Comparing three methods of handling multicollinearity using simulation approach by Adnan, Norliza

“…The algorithm is described and for the purpose of comparing the three methods, simulated data sets where the number of cases was less than the number of observations were used. …”
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Modifying maximum likelihood test for solving singularity and outlier problems in high dimensional cases by Hafeez, Ahmad

“…The performance of MLѡвсн and four more modified ML-tests, namely MLtests with banded Cholesky estimator MLвсн with Thresholding MLтн with Weiszfeld Algorithm MLѡ and with Weiszfeld’s Algorithm Estimator and Thresholding MLѡтн had been examined using Type I error and power of test values in a simulation study. …”
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A Modified Approach For Load Flow Analysis Of Integrated AC-DC Power Systems by Mustafa, M.W., Abd Kadir, Aida Fazliana

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Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems by Bashar AbedAl Mohdi Talal AlDeeb

“…(iv) In addition, IWD has two variables that have a large effect on the performance and the convergence of the algorithm (Alijla et al., 2013). …”

Use of AR Block Processing for Estimating the State Variables of Power System by Mohd Nor, Nursyarizal, Jegatheesan, Ramiah, Perumal, Nallagownden

“…Samples of the local utility network for 103-bus parameter are collected and simulated using Burg and Modified Covariance algorithm to estimate the state variables. …”
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Multigrid solution of Euler equations using high-resolution NVD differencing scheme for unstructured meshes by Ng K.C., Yusoff M.Z., Ng E.Y.K.

A Comparative Study On Some Methods For Handling Multicollinearity Problems by Adnan, Norliza, Ahmad, Maizah Hura, Adnan, Robiah

“…The algorithm is described and for the purpose of comparing the three methods, simulated data sets where the number of cases were less than the number of observations used. …”
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A comparative study on some methods for handling multicollinearity problems by Adnan, Norliza, Ahmad, Maizah Hura, Adnan, Robiah

“…The algorithm is described and for the purpose of comparing the three methods, simulated data sets where the number of cases were less than the number of observations used. …”
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Using adaptive safe experimentation dynamics algorithm for maximizing wind farm power by Mohd Ashraf, Ahmad, Jui, Julakha Jahan, Mohd Riduwan, Ghazali

“…This research presents a model-free strategy for increasing wind farm power generation based on the Adaptive Safe Experimentation Dynamics Algorithm (ASEDA). The ASEDA method is an improved version of the Safe Experimentation Dynamics (SED) algorithm that modifies the current tuning variable to respond to the changes in the objective function. …”
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Using Metaheuristics Algorithms (MHAs) to Optimize Water Supply Operation in Reservoirs: a Review by Almubaidin M.A.A., Ahmed A.N., Sidek L.B.M., Elshafie A.

Using adaptive safe experimentation dynamics algorithm for maximizing wind farm power production by Mohd Ashraf, Ahmad, Jui, Julakha Jahan, Mohd Riduwan, Ghazali

“…This research presents a model-free strategy for increasing wind farm power generation based on the Adaptive Safe Experimentation Dynamics Algorithm (ASEDA). The ASEDA method is an improved version of the Safe Experimentation Dynamics (SED) algorithm that modifies the current tuning variable to respond to the changes in the objective function. …”
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Development of fault detection, diagnosis and control system identification using multivariate statistical process control (MSPC) by Ibrahim, Kamarul 'Asri, Ahmad, Arshad, Ali, Mohamad Wijayanuddin, Mak, Weng Yee

“…In this research work, an FDD algorithm is developed using MSPC and correlation coefficients between process variables. …”
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