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Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method by Marlan Z.M., Jamaludin K.R., Harudin N.

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Cellular Automata-based Algorithm for Liquid Diffusion Phenomenon Modeling using imaging technique by Al-Ghaili, Abbas Mohammed Ali

“…This thesis proposes a dynamical behavior prediction algorithm using Cellular Automata (CA) to model the LDP. …”
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Artificial neural network model for predicting windstorm intensity and the potential damages / Mohd Fatruz Bachok by Bachok, Mohd Fatruz

“…The other 11 prediction processes which utilised ANN model algorithms (fitting tool), gave R-values for all the algorithms higher than 0.900 except one algorithm equal to 0.8661, meanwhile MSE between 0.22 to 116.41. …”
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Rock brittleness prediction through two optimization algorithms namely particle swarm optimization and imperialism competitive algorithm by Hussain, Azham, Surendar, A., Clementking, A., Kanagarajan, Sujith, Ilyashenko, Lubov K.

“…In the other words, four predictive models, namely ICA linear, ICA power, PSO linear, and PSO power models are developed to predict BI in this study. …”
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Rainfall prediction using multiple inclusive models and large climate indices by Mohamadi S., Sheikh Khozani Z., Ehteram M., Ahmed A.N., El-Shafie A.

Predicting breast cancer using ant colony optimisation / Siti Sarah Aqilah Che Ani by Che Ani, Siti Sarah Aqilah

“…This study implements a machine learning algorithm called Ant Colony Optimization (ACO) algorithm to develop an accurate classification model for predicting breast cancer cells. …”
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A genetic algorithm optimized RNN-LSTM model for remaining useful life prediction of turbofan engine by Chui, K.T., Gupta, B.B., Vasant, P.

“…Both feature extraction and prediction algorithm have played crucial roles on the performance of RUL prediction models. …”
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Predicting attackers of online shaming using ant colony optimization / Noor Shafiqa Fazlien Mohamad Fauzi by Mohamad Fauzi, Noor Shafiqa Fazlien

“…In order to predict the attackers of online shaming, Ant Colony Optimization Algorithm will be used and it will be compared with J48 algorithm. …”
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Optimization of Prediction Error in CO2 Laser Cutting process by Taguchi Artificial Neural Network Hybrid with Genetic algorithm by Nukman, Y., Hassan, M.A., Harizam, M.Z.

“…In some cases, the prediction errors of Taguchi ANN model was larger than 10 even with Levenberg Marquardt training algorithm. …”
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Laptop price prediction using decision tree algorithm / Nurnazifah Abd Mokti by Abd Mokti, Nurnazifah

“…This research project focuses on developing a laptop price prediction model using the decision tree algorithm based on laptop specifications. …”
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A hybrid model using genetic algorithm and neural network for predicting dengue outbreak by Husin, Nor Azura, Mustapha, Norwati, Sulaiman, Md. Nasir, Yaakob, Razali

“…The aim of this paper is to design a more promising model for predicting dengue outbreak by using a hybrid model based on genetic algorithm for the determination of weight in neural network model. …”
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Artificial neural network-salp-swarm algorithm for stock price prediction by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Azlan, Abdul Aziz

“…The dataset used for analyzing stock prices often displays complex patterns and high volatility, making the generation of accurate predictions difficult. To address these challenges, this study proposes a hybrid prediction model that combines the salp-swarm algorithm and the artificial neural network (SSA-ANN). …”
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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 Predicting Reservoir Water Level by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

“…Therefore, predicting water level needs robust models. Our study introduces a new model for predicting reservoir water levels. …”

An enhanced feed-forward neural networks and a rule-based algorithm for predictive modelling of students' academic performance by Raheem, Ajiboye Adeleke

“…Such enhancement would ensure a predictive network model that can generalize well with a set of untrained data. …”
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Predicting customer churn in telecommunication service provider industry using Random Forest / Wan Muhammad Naqib Zafran Wan Roslan by Wan Roslan, Wan Muhammad Naqib Zafran

“…This project addresses the challenge of customer churn in the Telecommunications Service Provider (TSP) industry by focusing on the Random Forest algorithm for predictive modeling. This study aims to throughly explore the Random Forest algorithm, develop a robust Random Forest customer churn predictive model, and evaluate its performance in predicting customer churn within the internet service provider sector. …”
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Integrated support vector regression and an improved particle swarm optimization-based model for solar radiation prediction by Ghazvinian H., Mousavi S.-F., Karami H., Farzin S., Ehteram M., Hossain M.S., Fai C.M., Hashim H.B., Singh V.P., Ros F.C., Ahmed A.N., Afan H.A., Lai S.H., El-Shafie A.

Octane number prediction for gasoline blends using convolution neural network / Zhu Yue by Zhu , Yue

“…With the development of information technology, the development of neural network plays an important role in the prediction of various situations in real life. At present, there are many prediction algorithms based on machine learning. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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A novel RSSI prediction using imperialist competition algorithm (ICA), radial basis function (RBF) and firefly algorithm (FFA) in wireless networks by Goudarzi, Shidrokh, Hassan, Wan Haslina, Hassan Abdalla Hashim, Aisha, Soleymani, Seyed Ahmad, Anisi, Mohammad Hossein, Zakaria, Omar M.

“…The prediction accuracy of the proposed IRBF–FFA model was validated by comparing it to support vector machines (SVMs) and multilayer perceptron (MLP) models. …”
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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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