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Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

Modeling of vehicle trajectory using K-means and fuzzy C-means clustering by Choong, Mei Yeen, Lorita Angeline, Chin, Renee Ka Yin, Yeo, Kiam Beng, Teo, Kenneth Tze Kin

“…Hence, the clustering of vehicle trajectory dataset for similar patterns identification is implemented with k-means and fuzzy c-means (FCM) clustering algorithm. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri by Mohd Sabri, Norlina

“…The first enhancement is the implementation of the mass ratio parameter as the Kbest agents. …”
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An efficient control implementation for inverter based harmony serach algorithm by Najeeb, Mushtaq, Hamdan, Daniyal, Ramdan, Razali, Muhamad, Mansor

“…The HS algorithm aims to handle the trial and error procedure used in finding the PI parameters and then apply the proposed control algorithm via the eZdsp TMS320F28355 board to link the inverter prototype with the Matlab Simulink. …”
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ADAPTIVE LINEAR ALGORITHMS FOR POWER SYSTEM FUNDAMENTAL AND HARMONIC ESTIMATION by MUBARAK MOHMMED, HUSSAM ALHAJ

“…On the other hand, Least Mean Square (LMS) algorithm is known for its ease of structure, computation and simplicity. …”
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Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network by Abdulrazzak H.N., Hock G.C., Mohamed Radzi N.A., Tan N.M.L., Kwong C.F.

“…The evaluation process was implemented on RK-Means, K-Means++, and OK-Means models. …”

An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis by Tie, K. H., A., Senawi, Chuan, Z. L.

“…However, different clustering algorithms have different parameters that need to be specified. …”
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Effectiveness of Nature-Inspired Algorithms using ANFIS for Blade Design Optimization and Wind Turbine Efficiency by Sarkar, Md Rasel, Julai, Sabariah, Chong, Wen Tong, Toha, Siti Fauziah

“…In addition, an adaptive neuro-fuzzy interface (ANFIS) approach is implemented to predict the Cp of wind turbine blades for investigation of algorithm performance based on the coefficient determination (R 2 ) and root mean square error (RMSE). …”
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An Efficient Control Implementation for Inverter Based Harmony Search Algorithm by Najeeb, Mushtaq, Hamdan, Daniyal, Ramdan, Razali, Muhamad, Mansor

“…The HS algorithm aims to handle the trial and error procedure used in finding the PI parameters and then apply the proposed control algorithm via the eZdsp TMS320F28355 board to link the inverter prototype with the Matlab Simulink. …”
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Experimental implementation controlled SPWM inverter based harmony search algorithm by Najeeb M., Mansor M., Razali R., Daniyal H., Yahaya J.A.F.

Effectiveness of nature-inspired algorithms using ANFIS for blade design optimization and wind turbine efficiency by Sarkar, Md. Rasel, Julai, Sabariah, Chong, Wen Tong, Toha @ Tohara, Siti Fauziah

“…In addition, an adaptive neuro-fuzzy interface (ANFIS) approach is implemented to predict the Cp of wind turbine blades for investigation of algorithm performance based on the coefficient determination (R2) and root mean square error (RMSE). …”
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Experimental implementation controlled SPWM inverter based harmony search algorithm by Najeeb, Mushtaq, Mansor, Muhamad, Razali, Ramdan, Daniyal, Hamdan, A. F. Yahaya, Jabbar

“…The mean absolute error (MAE) formula is used as an objective function with the HS algorithm in finding the adaptive values of  and  parameters to minimize the error of the inverter output voltage. …”
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Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

“…In other words, the implemented bat algorithm in neural network structure is to get global optimization in order to minimize mean absolute percentage error, MAPE. …”
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Detection of the spread of Covid-19 in Indonesia using K-Means Clustering Algorithm / Mohammad Yazdi Pusadan ... [et al.] by Pusadan, Mohammad Yazdi, Rabbani, Mohammad Abied, Ardiansyah, Rizka, Ngemba, Hajra Rasmita

“…The implementation of the K-Means Clustering algorithm for detecting the level of spread of COVID-19 data in Indonesia by using the parameter k=3 is quite good with areas in Indonesia that have a high the spread of COVID-19 and the results of the cluster validity test get silhouette values on O = (Total Case, Total Death) and P = (Total Case, Total Death, Total Recovered) have the same cluster value, which is 0.93 which means the cluster quality is very good.…”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Tay, Kim Gaik, Huong, Audrey, Sathasivam, Saratha, Majahar Ali, Majid Khan

“…Each of these methods is presented in the steps in the flowchart form which can be used for its straightforward implementation in any programming language. With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Real time nonlinear filtered-x lms algorithm for active noise control by Sahib, Mouayad Abdulredha

“…The performance of these algorithms is usually compared with the standard linear filtered-x least mean square (FXLMS) algorithm. …”
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A method for computation of surface roughness of digital elevation model terrains via multiscale analysis by Ahmad Fadzil, Mohamad Hani, Sathyamoorthy, Dinesh, Asirvadam, Vijanth Sagayan

“…The selected case studies of the algorithm implementation demonstrated that the proposed algorithm provides a surface roughness parameter that is realistic with respect to the amplitudes and frequencies of the terrain, invariant with respect to rotation and translation, and has intuitive meaning. …”
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A method for computation of surface roughness of digital elevation model terrains via multiscale analysis by Mohd Hani, Ahmad Fadzil, Sathyamoorthy, Dinesh, Asirvadam , Vijanth Sagayan

“…The selected case studies of the algorithm implementation demonstrated that the proposed algorithm provides a surface roughness parameter that is realistic with respect to the amplitudes and frequencies of the terrain, invariant with respect to rotation and translation, and has intuitive meaning. …”
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Perovskite lattice constant prediction framework using optimized artificial neural network and fuzzy logic models by metaheuristic algorithms by Bouzateur, Inas, Ouali, Mohammed Assam, Bennacer, Hamza, Ladjal, Mohamed, Khmaissia, Fadoua, Rahman, Mohd Amiruddin Abd, Boukortt, Abdelkader

“…In the first part, the study assessed, the effectiveness of various metaheuristic algorithms (PSO-IWO-ICA) in tuning the parameters of the ANN prediction structure in order to get the optimal parameter of the ANN. …”
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