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Reinforcement Learning Algorithm for Optimising Durian Irrigation Systems: Maximising Growth and Water Efficiency by Ramli, Muhammad Shahrul Azwan, Zainal Abidin, Mohamad Shukri, Hasan, Nor Shahida, Md Reba, Mohd Nadzri, Kolawole, Keshinro Kazeem, Ardiansyah, Rizqi Andry, Mpuhus, Sikudhan Lucas

“…The algorithm was developed by calibrating the AQUACROP model using data from actual durian plantations where rain-fed irrigation (rain-fed) was practised. …”
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr... by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

“…For water level prediction, lagged rainfall and water level are used. In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”

Combination of perturb and observe with online sequential extreme learning machine for photovoltaic system maximum power point tracking by Dira, Yasir Sabah

“…From different MPPT techniques previously proposed, the online sequential extreme learning machine algorithm and conventional perturb and observe are combined together as a proposed MPPT algorithm. …”
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Random forest algorithm for co2 water alternating gas incremental recovery factor prediction by Belazreg, L., Mahmood, S.M., Aulia, A.

“…The aim of this paper is using an ensemble machine learning algorithm to develop a WAG incremental recovery factor predictive model that can be used by reservoir engineers to estimate WAG incremental recovery factor prior kick-off of laboratory experiments and comprehensive technical studies. …”
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Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia by Lay, Usman Salihu

“…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
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Box-jenkins and genetic algorithm hybrid model for electricity forecasting system by Mahpol, Khairil Asmani

“…By adopting the GA blind search, the algorithm combines searching techniques and their capabilities to learn about the relationship of the pattern-recognition of the past data. …”
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Visual analysis to investigate the capability of ANFIS in modelling hydrological relationship using synthetic dataset by Ngahzaifa, Ab. Ghani, Zuriani, Mustaffa, Zafril Rizal, M Azmi

“…In hydrology especially, every process is unique and dependent on large number of natural factors hence modelling using machine learning algorithm without considering hydrological insight is very dangerous. …”
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Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques by Farhan, Farhan Abdel-Fattah Ahmad

“…The proposed algorithm employs a combined model that uses two different measures (nonconformity metric measures and Local Distance-based Outlier Factor (LDOF)) to improve its detection ability. …”
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Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower by Gatea, Sarah Jabbar

“…The results are used to develop the hybrid learning algorithm based on the AdaBoost, Bagging, and RUSBoost methods to predict the damage in the tower based on dynamic frequency domain. …”
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Logic Mining Approach: Shoppers’ Purchasing Data Extraction via Evolutionary Algorithm by Mohd Kasihmuddin, Mohd Shareduwan, Abdul Halim, Nur Shahira, Mohd Jamaludin, Siti Zulaikha, Mansor, Mohd. Asyraf, Alway, Alyaa, Zamri, Nur Ezlin, Azhar, Siti Aishah, Marsani, Muhammad Fadhil

“…In reducing the learning complexity, a genetic algorithm was implemented to optimize the logical rule throughout the learning phase in performing a 2-satisfiability-based reverse analysis method, implemented during the learning phase as this method was compared. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. …”
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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

“…Data collected were used for the multilevel analysis, Markov Chain Monte Carlo (MCMC) simulation via WinBUGS algorithm and influence diagrams for BBNs. …”
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

“…Moreover, K-Nearest Neighbor (KNN) classifier was used to evaluate the effectiveness of the features identified by the proposed SCSO algorithm. …”
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The effect of pre-processing techniques and optimal parameters on BPNN for data classification by HUSSEIN, AMEER SALEH

“…Most existing approaches modify the learning model in order to add a random factor to the model which can help to overcome the tendency to sink into local minima. …”
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Performance optimization of the parabolic trough power plant using a dual-stage ensemble algorithm by Elfeky K.E., Hosny M., Mohammed A.G., Chu W., Khatwa S.A., Wang Q.

Feature selection and optimal neural network algorithm for the state of charge estimation of lithium-ion battery for electric vehicle application by Hossain Lipu M.S., Hannan M.A., Hussain A.

Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy by Hossain, Ishtiaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

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A functional link neural network with modified cuckoo search for prediction tasks by Abu Bakar, Siti Zulaikha

“…Therefore, prediction of temperature and relative humidity is an important factor to measure the environmental changes. Neural network, especially the Multi-Layer Perceptron (MLP) which uses Back Propagation algorithm (BP) as a supervised learning method, has been successfully applied in various problems for meteorological prediction tasks. …”
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Dynamic and adaptive execution models for data stream mining applications in mobile edge cloud computing systems / Muhammad Habib Ur Rehman by Muhammad Habib , Ur Rehman

“…However, the execution of MDSM applications in MECC systems becomes hard due to multiple factors. The critical factors of complexity at application level include data size and data rate of continuously streaming data, the selection of data fusion and data preprocessing methods, the choice of learning models, learning rates and learning modes, and the adoption of data mining algorithms. …”
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An acquisition and a modulated recognition system for driver profiling in Malaysia / Ward Ahmed Alaulddin Al-Hussein by Ward Ahmed Alaulddin , Al-Hussein

“…The process of collecting driving data and using a computational model to generate a safety score for the driver is known as driver profiling. …”
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