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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

“…The class imbalance makes estimating building damage grades difficult, emphasizing the necessity for careful modeling. Bayesian Optimization optimizes machine learning algorithm hyperparameters to solve this problem. …”
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New bio-inspired barnacle optimizers based least-square support vector machine for time-series prediction of pandemic outbreaks by Marzia, Ahmed

“…Firstly, this thesis proposes hybrid optimized machine learning models by combining improved BMO variants with Least Squares Support Vector Machines (LSSVM) to effectively capture intricate temporal patterns. …”
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EEG-based emotion recognition using machine learning algorithms by Lam, Yee Wei

“…Training will be conducted so the model can learn and capture patterns of data. Moreover, fine-tuning of model will be applied to get the optimal performance in machine learning model. …”
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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.

“…This paper introduces a novel prediction hybrid model based on singular spectrum analysis (SSA), adaptive beluga whale optimization (ABWO), and an improved extreme learning machine (IELM). …”
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Lexicon-based and immune system based learning methods in Twitter sentiment analysis by Jantan, Hamidah, Drahman, Fatimatul Zahrah, Alhadi, Nazirah, Mamat, Fatimah

“…In future work, the accuracy of proposed model can be strengthened by comparative study with other heuristic based searching algorithms such as genetic algorithm, ant colony optimization, swam algorithms and etc.…”
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Optimize and deploy machine learning algorithms on embedded devices for manufacturing applications by Teoh, Ming Xue

“…This proposal discusses the techniques of optimizing and deploying machine learning algorithms on embedded devices for manufacturing applications; We investigate problems of printed circuit board (PCB) defects and artificial intelligence in embedded system. …”
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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.

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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. …”

Development of prediction model for phosphate in reservoir water system based machine learning algorithms by Latif S.D., Birima A.H., Ahmed A.N., Hatem D.M., Al-Ansari N., Fai C.M., El-Shafie A.

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

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

“…Benchmarking; Classification (of information); Constrained optimization; Decision making; Electric power systems; Iterative methods; Knowledge acquisition; Learning algorithms; Pattern recognition; Probability; Confidence threshold; Decision making process; Extreme learning machine; Machine learning approaches; Pattern classification problems; Post-processing procedure; Power system applications; Probabilistic output; Machine learning…”

Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system by Maseer, Ziadoon Kamil

“…The optimized DBN algorithm, known as the HW-DBN algorithm, integrated through feature learning based on a Gaussian–Bernoulli Restricted Boltzmann Machine as well as classification task through a weight neuron network. …”
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Evaluation of deep learning algorithm for inflow forecasting: a case study of Durian Tunggal Reservoir, Peninsular Malaysia by Latif S.D., Ahmed A.N., Sathiamurthy E., Huang Y.F., El-Shafie A.

Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network by Sivarao, Subramonian

“…Therefore, prediction of laser machining cut quality, namely surface roughness was carried out using machine learning techniques based on Quick Back Propagation Algorithm using ANN. …”
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud by Shariff, S. Sarifah Radiah, Hud, Hady

“…Secondly, in solving every Machine Learning problem, there is no one algorithm superior to other algorithms. …”
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A comprehensive comparison of recent developed meta-heuristic algorithms for streamflow time series forecasting problem by Ahmed A.N., Van Lam T., Hung N.D., Van Thieu N., Kisi O., El-Shafie A.

A new model for iris data set classification based on linear support vector machine parameter's optimization by Faiz Hussain, Zahraa, Ibraheem, Hind Raad, Alsajri, Mohammad, Ali, Ahmed Hussein, Mohd Arfian, Ismail, Shahreen, Kasim, Sutikno, Tole

“…The SVM is a one technique of machine learning techniques that is well known technique, learning with supervised and have been applied perfectly to a vary problems of: regression, classification, and clustering in diverse domains such as gene expression, web text mining. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling by Alfred, Rayner, Loo, Yew Jie, Obit, Joe Henry, Lim, Yuto, Haviluddin, Haviluddin, Azman, Azreen

“…Recently, several effective supervised and unsupervised machine learning methods have been developed in the domain of topics extraction. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

“…The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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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. …”
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