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

A New Probabilistic Output Constrained Optimization Extreme Learning Machine by Wong S.Y., Yap K.S., Li X.C.

Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant by Morshidi, Malik Arman

“…Results of studying color segmentation using machine-learning algorithm and color space analysis is presented in this thesis. …”
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Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms by Al-Rawashdeh, Mohammad, Al Nawaiseh, Moh’d, Yousef, Isam, Bisharah, Majdi, Alkhadrawi, Sajeda, Al-Bdour, Hamza

“…Bayesian Optimization optimizes machine learning algorithm hyperparameters to solve this problem. …”
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Machine Learning in accounting: an introduction / Wan Mardyatul Miza Wan Tahir and Jaízah Abdul Jabar by Wan Tahir, Wan Mardyatul Miza, Abdul Jabar, Jaízah

“…Machine Learning is an application of Artificial Intelligence (AI) in which computers use algorithms to learn and recognise patterns. …”
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Machining surface roughness monitoring using acoustic emission method by Mohd Syazlan, Mohd Hatta

“…The objective of this project is to collect the data acquisition of the experiment by operating milling process, to study the correlation of AE parameter with work piece surface quality by comparing the AE signals with average roughness, Ra of the work piece’s surface measured by using Perthometer, and to develop algorithm for online machining condition monitoring. …”
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Constrained–Optimization-based Bayesian posterior probability extreme learning machine for pattern classification by Wong S.Y., Yap K.S.

“…Extreme Learning Machine (ELM) has drawn overwhelming attention from various fields notably in neural network researches for being an efficient algorithm. …”

Condition monitoring of deep drilling process for cooling channel making in hot press die by Muhamad Aslam, Abdul Raub

“…SVM performs classification process based on the data input vector that comprise as fault in the machine. The fault is then being produced as the pattern and SVM will recognize thus classify this pattern corresponding to the fault. …”
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A novel hybrid photovoltaic current prediction model utilizing singular spectrum analysis, adaptive beluga whale optimization, and improved extreme learning machine by Mohammed Ridha, Hussein, Ahmadipour, Masoud, Alghrairi, Mokhalad, Hizam, Hashim, Mirjalili, Seyedali, Zubaidi, Salah L., Mohammed S, Marwa Y.

“…The precise and accurate prediction of the photovoltaic (PV) system can ensure the grid-connected system's constant operation and defect-free performance. Nonetheless, the PV current system's chaotic output is compounded by unpredictable weather patterns, which lead to poor predict stability, accuracy, and increasing costs. …”
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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, Koting, Suhana, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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A design of machine vision system for the automatic surface profiling measurement using shadow moire technique / Lim Teong Yeong, Lim Juinn Hsuh and Muhamad Othman. by Lim, Teong Yeong, Lim, Juinn Hsuh, Othman, Muhamad

“…In this research the surface profiling measurement using the shadow moire technique with phase-shifting algorithms has been implemented. A simple surface profiling machine setup has been introduced and fabricated by using the machine vision principle and the moire experimentation. …”
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On equivalence of FIS and ELM for interpretable rule-based knowledge representation by Wong S.Y., Yap K.S., Yap H.J., Tan S.C., Chang S.W.

Performance optimization on axial-flux permanent magnet coreless generator using novel hybrid computational method based on genetic algorithm and pattern search / Lok Choon Long by Lok , Choon Long

“…Improved hybrid optimization method using Pattern Search (PS) and Genetic Algorithm (GA) onto Axial-Flux Permanent Magnet (AFPM) Coreless generator is presented in this thesis, and the optimization is based on the popular multi-objective sizing equation. …”
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Optimal energy management strategies for hybrid electric vehicles : A recent survey of machine learning approaches by Jui, Julakha Jahan, Mohd Ashraf, Ahmad, Molla, Md Mamun, Muhammad Ikram, Mohd Rashid

“…We emphasize how machine learning algorithms may be adjusted to dynamic operating environments, how well they can identify intricate patterns in hybrid electric vehicle systems, and how well they can manage non-linear behaviors.…”
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A review of the hybrid artificial intelligence and optimization modelling of hydrological streamflow forecasting by Ibrahim K.S.M.H., Huang Y.F., Ahmed A.N., Koo C.H., El-Shafie A.

Apply and optimize machine learning algorithms for estimating battery health by Chin, Wai Yee

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Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat by Chia , Yu Huat

“…This is due to the data generated from the numerical model possess the pattern for the ML algorithm ease of prediction. In addition, Coati Optimization algorithm, Particle Swarm Opimisation (PSO) and Bayesian Optimsiation (BO) are integrated to identify optimal parameters and minimize settlement during twin tunnel excavation and GBT with the optimisation algorithm has shown consistent capability identifying the least SS induced by twin tunnels Keyword: …”
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River flow prediction based on improved machine learning method: Cuckoo Search-Artificial Neural Network by Zanial W.N.C.W., Malek M.B.A., Reba M.N.M., Zaini N., Ahmed A.N., Sherif M., Elshafie A.

“…Therefore, it is necessary to precisely estimate how the river flow will alter as a result of changing rainfall patterns. Finding the best value for the hyper-parameters is one of the problems with machine learning algorithms, which have lately been adopted by many academics. …”

A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

“…Data analysis, data reduction, approxi mate classification, machine learning, and discovery of pattern in data are functions performed by a rough sets analysis. …”
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1D CNN Model for Corrosion Prediction by Zaini, Nurfaraheen

“…Besides, it is to develop a machine learning of predictive analytics algorithm with a visualization dashboard for the predicted of internal and external corrosion levels of pipelines. …”
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