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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

“…The focus of the paper is to propose a hybrid approach for the selection of the most influential input variables for the training and testing of neural network based hybrid models. …”
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Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks by Islam, B., Baharudin, Z., Nallagownden, P.

“…A hybrid approach that combines ANN and an evolutionary optimization technique, genetic algorithm (GA) is used for the development of a short term load forecast (STLF) model. …”
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A memory optimal BFGS neural network training algorithm by McLoone, Sean, Asirvadam , Vijanth Sagayan

“…This paper considers the implementation of a novel memory optimal neural network training algorithm which maximises performance in relation to available memory. …”
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Dynamic point stochastic rounding algorithm for limited precision arithmetic in Deep Belief Network training by Essam, M., Tang, T.B., Ho, E.T.W., Chen, H.

“…Using publicly available MNIST database, we show that the proposed algorithm can train a 3-layer DBN with an average accuracy of 98.49, with a drop of 0.08 from the double floating-point average accuracy. © 2017 IEEE.…”
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Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA) by Mohiuddin, A. K. M., Ashour, Ahmed Aly Ibrahim Shaaban, Yap, Haw Shin

“…The primary concern is to acquire the clear picture of the implementation of Multi-Objective Genetic Algorithm and the essential of variable valve timing effects on the engine performances in various engine speeds. …”
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SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

“…The crucial part about MLP is the learning or training process in which the weights are tuned on the presence of input data to produce a reliable and accurate estimation. …”
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Multidimensional Minimization Training Algorithms for Steam Boiler Drum Level Trip Using Artificial Intelligence Monitoring System by Ismail, F. B., Al-Kayiem, Hussain H.

“…The one hidden layer with one neuron using BFG training algorithm provides the best optimum neural network structure. …”
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Power plant energy predictions based on thermal factors using ridge and support vector regressor algorithms by Afzal, Asif, Alshahrani, Saad, Alrobaian, Abdulrahman, Buradi, Abdulrajak, Khan, Sher Afghan

“…It is concluded that these algorithms are suitable for predicting sensitive output energy data of a CCPP depending on thermal input variables.…”
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Prediction of Machine Failure by Using Machine Learning Algorithm by Fakhrurazi, Nur Amalina

“…Then, the data is cluster by using K Means to produce labeled input that will be trained by using Gradient Boosting Machine, a decision tree algorithm to make prediction. …”
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Machine Learning Classifications of Multiple Organ Failures in a Malaysian Intensive Care Unit by Shah N.N.H., Razak N.N.A., Razak A.A., Abu-Samah A., Suhaimi F.M., Jamaluddin U.

Enhancing obfuscation technique for protecting source code against software reverse engineering by Mahfoudh, Asma

“…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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Enhancing the entrepreneurial intention of the retiring military personnel through entrepreneurial training by Yusuf, Lamidi

“…This study examined the factors enhancing the entrepreneurial intention of the retiring military personnel in Nigeria, using entrepreneurial training as a moderator. A total of 423 retiring military personnel on pre-retirement entrepreneurial and vocational training programme at the Nigerian Armed Forces Resettlement Centre, Oshodi, Lagos, Nigeria participated in the study. …”
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Application of Hybrid Evolutionary Algorithm and thematic map for rule set generation and visualization of chlorophyta abundance at Putrajaya lake / Lau Chia Fong by Lau, Chia Fong

“…HEA is run on the training set in order to provide insights on the relationships between input variables and the algae abundance. …”
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Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network by Mohd Hamdan, Eleena Yasmeen

“…As for the implementation of MPCA in feature extraction for BOD and COD, there were only 4 inputs required to explain at least 99.999% variability for both analyses. Altogether, for BOD, the BR algorithm with 60% training and 12 hidden nodes gives R=0.7825 whereas for COD, the BR algorithm with 70% training and 10 hidden nodes gives R=0.6716. …”
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Predicting dengue transmission rates by comparing different machine learning models with vector indices and meteorological data by Ong, Song Quan, Pradeep Isawasan, Ahmad Mohiddin Mohd Ngesom, Hanipah Shahar, As’malia Md Lasim, Gomesh Nair

“…Previous work has focused only on specific weather variables and algorithms, and there is still a need for a model that uses more variables and algorithms that have higher performance. …”
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Evaluating enhanced predictive modeling of foam concrete compressive strength using artificial intelligence algorithms by Abdellatief M., Wong L.S., Din N.M., Mo K.H., Ahmed A.N., El-Shafie A.

“…Therefore, it is recommended to utilize the prediction algorithms within the range of input variables employed in this investigation for optimal results. ? …”

Neural network based model predictive control for a steel pickling process by Kittisupakorn, P., Thitiyasook, P., Hussain, Mohd Azlan, Daosud, W.

“…The Levenberg-Marquardt algorithm is used to train the process models. In the control (MPC) algorithm, the feedforward neural network models are used to predict the state variables over a prediction horizon within the model predictive control algorithm for searching the optimal control actions via sequential quadratic programming. …”
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Developing a model to predict mathematics performance using neural network / Normaziah Abdul Rahman, Fadzilah Siraj and Noor Aishikin Adam by Abdul Rahman, Normaziah, Siraj, Fadzilah, Adam, Noor Aishikin

“…A total of 391 data samples of diploma students were collected, trained and tested using this model. …”
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Feasibility analysis for predicting the compressive and tensile strength of concrete using machine learning algorithms by Ziyad Sami B.H., Ziyad Sami B.F., Kumar P., Ahmed A.N., Amieghemen G.E., Sherif M.M., El-Shafie A.

“…The model had an impressive performance during the training phase, with a R2 of 0.98, RMSE of 2.412 MPa, and MAE of 1.6249 MPa when using 8 input variables to predict the compressive strength of concrete. …”

A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…The firefly algorithm remains a feasible alternative for shallow architectural network models, while metaheuristic algorithms such as the Particle swarm algorithm and Bat algorithm are better options for deeper architectural network models. …”
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