Search Results - predicting _ (differences OR difference) (evolution OR solution) algorithm

Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia by Zubaidi S.L., Kumar P., Al-Bugharbee H., Ahmed A.N., Ridha H.M., Mo K.H., El-Shafie A.

“…Hybrid model development included the optimization of ANN coefficients (its weights and biases) using adaptive guided differential evolution algorithm. Post-optimization ANN model was trained using eleven different leaning algorithms. …”

Machine learning modeling for radiofrequency electromagnetic fields (RF-EMF) signals from mmWave 5G signals by Al-Jumaily, Abdulmajeed, Sali, Aduwati, Riyadh, Mohammed, Wali, Sangin Qahtan, Li, Lu, Osman, Anwar Faizd

“…As a result, it can be observed that the Exact-RBFNN algorithm is the best algorithm to predict the RF-EMF because it shows good agreement with the measured value. …”
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Identification and predictive control of spray tower system using artificial neural network and differential evolution algorithm by Danzomo, Bashir A., Salami, Momoh Jimoh Eyiomika, Khan, Md. Raisuddin

“…This includes the use of an artificial neural network (ANN) based predictive control strategy and differential evolution (DE) optimization algorithm to determines the optimal control signal, uk (liquid droplet size, dD) by minimizing the cost function such that the output is set below the allowable PM concentration. …”
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Application of the hybrid ANFIS models for long term wind power density prediction with extrapolation capability by Hossain, Monowar, Mekhilef, Saad, Afifi, Firdaus, Halabi, Laith M., Olatomiwa, Lanre, Seyedmahmoudian, Mehdi, Horan, Ben, Stojcevski, Alex

“…For this aim, standalone ANFIS, ANFIS-PSO, ANFIS-GA and ANFIS-DE prediction algorithm are developed in MATLAB platform. …”
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A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat by Sakamat, Norzehan

“…Recognition software achieved 87.14%, EPD algorithm achieved 73.57% and HMT algorithm achieved 74.30%) prediction accuracy with OTs. …”
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Evaluation of machine learning algorithms in predicting CO 2 internal corrosion in oil and gas pipelines by Mohammad Zubir, W.M.A., Abdul Aziz, I., Jaafar, J.

“…The empirical solutions also lack intelligence in adapting to different environment. …”
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Evaluation of machine learning algorithms in predicting CO2 internal corrosion in oil and gas pipelines by Mohammad Zubir, W.M.A., Abdul Aziz, I., Jaafar, J.

“…The empirical solutions also lack intelligence in adapting to different environment. …”
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Parameter extraction of solar photovoltaic modules using penalty-based differential evolution by Ishaque, K., Salam, Z., Mekhilef, Saad, Shamsudin, A.

“…This paper proposes a penalty based differential evolution (P-DE) for extracting the parameters of solar photovoltaic (PV) modules at different environmental conditions. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

“…This study recommends a selection trade-off as the function of prediction efficiency and efficacy of the algorithm. …”
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Hysteresis Modelling of Pneumatic Artificial Muscle using General Cubic Equation and Factor Theorem Prediction Method / Mohd Azuwan Mat Dzahir...[et al.] by Mat Dzahir, Mohd Azuwan, Mat Dzahir, Mohd Azwarie, Hussein, Mohamed, Ahmad, Zair Asrar, Mohamad, Maziah, Mad Saad, Shaharil

“…Rather than using a very complicated algorithm for control system of the pneumatic artificial muscle, a simple and noble prediction method using general cubic equation and factor theorem is proposed for the hysteresis modelling at different loads. …”
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Tumor growth prediction using parallel computing: numerical solutions based on multi-dimensional partial differential equation (PDE) by Alias, Norma, Islam, Md. Rajibul

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An exponential based simulated kalman filter algorithm for data-driven PID tuning in liquid slosh controller by Mohd Falfazli, Mat Jusof, Ahmad Nor Kasruddin, Nasir, Mohd Ashraf, Ahmad, Zuwairie, Ibrahim

“…The EbSKF is compared with the original SKF algorithm. In this study, 30 independent runs are performed to record different values of the best solutions generated by the algorithms of interest. …”
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Optimized adaptive neuro-fuzzy inference system using metaheuristic algorithms: Application of shield tunnelling ground surface settlement prediction by Liu, Xinni, Hussein, Sadaam Hadee, Kamarul Hawari, Ghazali, Tung, Tran Minh, Yaseen, Zaher Mundher

“…The predictive models were various nature-inspired frameworks, such as differential evolution (DE), particle swarm optimization (PSO), genetic algorithm (GA), and ant colony optimizer (ACO) to tune the adaptive neuro-fuzzy inference system (ANFIS). …”
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Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool by Samuel Simbine, Augusto

“…EDI GmbH in collaboration with Karlsruhe Institute of Technology (KIT) are working on the solution (AI-based tool for predictive process optimization for chemical plants) for the above-mentioned problem. …”
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Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

“…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

“…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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Depth linear discrimination-oriented feature selection method based on adaptive sine cosine algorithm for software defect prediction by Nasser, Abdullah, H.M. Ghanem, Waheed Ali, H.Y. Saad, Abdul-Malik, Hamed Abdul-Qawy, Antar Shaddad, A. Ghaleb, Sanaa A, Mohammed Alduais, Nayef Abdulwahab, Din, Fakhrud, Ghetas, Mohamed

“…Combining the simplicity of the SCA with the efficiency of multiple mutation operators inspired by Genetic Algorithms (GA), ASCA enhances the diversity of the solutions and imparts remarkable adaptability to various situations. …”
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Customer purchase prediction and product recommendations by Wong, Ji Hin

“…The third objective is to integrate customer purchase prediction and market basket analysis to provide different product recommendations for different customer groups. …”
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Performance evaluation of hybrid adaptive neuro-fuzzy inference system models for predicting monthly global solar radiation by Halabi, Laith M., Mekhilef, Saad, Hossain, Monowar

“…In this paper, standalone adaptive neuro-fuzzy inference system and hybrid models have been developed to predict monthly global solar radiation from different meteorological parameters such as sunshine duration S(h), and air temperature. …”
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An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction by Shah, Habib

“…Furthermore, here these algorithms used to train the MLP on two tasks; the seismic event's prediction and Boolean function classification. …”
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