Search Results - (( water distribution function algorithm ) OR ( parameter realization _ algorithm ))

Investigation of cross-entropy-based streamflow forecasting through an efficient interpretable automated search process by Chong K.L., Huang Y.F., Koo C.H., Sherif M., Ahmed A.N., El-Shafie A.

Estimation of the denitrification in the lower Mississippi Valley by Saleh, Abdul Razak

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Realization of microcontroller-based polarization control system with genetic algorithm by Mamdoohi, Ghazaleh, Esmaeilian-Marnani, Aida, Abas, Ahmad Fauzi, Samsudin, Khairulmizam, Hidayat, Ariya, Ibrahim, Noor Hisham, Mahdi, Mohd Adzir

“…To reach optimum performance, the code is optimized by using the best genetic parameter to achieve the fastest execution time. This algorithm consumes low size of memory besides providing fast speed. …”
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Parameter-Less Simulated Kalman Filter by Nor Hidayati, Abdul Aziz, Zuwairie, Ibrahim, Nor Azlina, Ab. Aziz, Saifudin, Razali

“…Further studies on the effect of P(0), Q and R values suggest that the SKF algorithm can be realized as a parameter-less algorithm. …”
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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

“…In this study, a new metaheuristic algorithm, viz., Grey Wolf Optimizer (GWO), is employed to optimize the parameters of interest. …”
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Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

“…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). This method was demonstrated for the optimization of machining parameters for turning operation using conventional lathe machines. …”
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Master-leader-slave cuckoo search with parameter control for ANN optimization and its real-world application to water quality prediction by Jaddi N.S., Abdullah S., Malek M.A.

Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning by Masuyama, Naoki, Loo, Chu Kiong, Ishibuchi, Hisao, Kubota, Naoyuki, Nojima, Yusuke, Liu, Yiping

“…In contrast, the proposed algorithm realizes a stable computation and reduces the number of parameters compared to existing algorithms. …”
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Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms by Hossain S.K.S., Ali S.S., Rushd S., Ayodele B.V., Cheng C.K.

Optimizing crystal size distribution based on different cooling strategies in batch crystallization process by Siti Zubaidah, Adnan, Noor Asma Fazli, Abdul Samad

“…The crystallization process was developed and simulated in Matlab software using a potash alum in the water system. Four optimization algorithms were proposed with different objective functions, such as maximizing mean crystal size (I), minimizing coefficient of variation (II), minimizing nucleus-grown crystals (III), and maximizing CSD (IV). …”
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Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S.

“…The leakage fault cases verify the algorithm�s applicability and complete the correlation diagnosis of water wall leakage fault. …”

Feedforward artificial neural network-based model for predicting the removal of phenolic compounds from water by using deep eutectic solvent-functionalized CNTs by Ibrahim R.K., Fiyadh S.S., AlSaadi M.A., Hin L.S., Mohd N.S., Ibrahim S., Afan H.A., Fai C.M., Ahmed A.N., Elshafie A.

Baseline trace metals in water and sediment of the Baleh River—a tropical river in Sarawak, Malaysia by Siong, Fong Sim, Hui, Ping Chai, Lee, Nyanti, Teck, Yee Ling, Jongkar, Grinang

“…The background values derived using the iterative 2σ algorithm and calculated distribution function were relatively lower. …”
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Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction by Zuriani, Mustaffa

“…The combination of lvABC and cmABC algorithm, which is later introduced as Enhanced Artificial Bee Colony–Least Squares Support Vector Machine (eABC-LSSVM), is realized in prediction of non renewable natural resources commodity price. …”
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Rice Predictive Analysis Mechanism Utilizing Grey Wolf Optimizer-Least Squares Support Vector Machines by Zuriani, Mustaffa, M. H., Sulaiman

“…In this regard, this study proposes a hybridization of LSSVM with a new Swarm Intelligence (SI) algorithm namely, Grey Wolf Optimizer (GWO). With such hybridization, the hyper-parameters of interest are automatically optimized by the GWO. …”
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Dengue outbreak prediction: hybrid meta-heuristic model by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Ernawan, Ferda, Yuhanis, Yusof, Mohamad Farhan, Mohamad Mohsin

“…Here, the FPA is served as an optimization algorithm for LSSVM. The hybrid FPA-LSSVM is later realized for prediction of dengue outbreak in Yogyakarta, Indonesia. …”
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Improving PID controller of motor shaft angular position by using genetic algorithm by Muhamad, Arif Abidin

“…This study represents Genetic Algorithm optimization of PID parameters gain in model reference robust control system structure for desired position of incremental servomotor. …”
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Reduced Fuzzy Recursive Least-Squares Algorithm For Real Time Estimation by Cheah, Kah Wai

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Application of LSSVM by ABC in energy commodity price forecasting by Mustaffa, Zuriani, Yusof, Yuhanis, Kamaruddin, Siti Sakira

“…The importance of the hyper parameters selection for a kernel-based algorithm, viz.Least Squares Support Vector Machines (LSSVM) has been a critical concern in literature.In order to meet the requirement, this work utilizes a variant of Artificial Bee Colony (known as mABC) for hyper parameters selection of LSSVM.The mABC contributes in the exploitation process of the artificial bees and is based on Levy mutation.Realized in crude oil price forecasting, the performance of mABC-LSSVM is guided based on Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSPE) and compared against the standard ABC-LSSVM and LSSVM optimized by Genetic Algorithm. …”
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Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms by Loo, C.K., Liew, W.S., Seera, M., Lim, Einly

“…The issues addressed are the sequence of training data for supervised learning and optimum parameter tuning for parameters such as baseline vigilance. …”
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