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An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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New Algorithm of Location Model based on Robust Estimators and Smoothing Approach by Hamid, Hashibah

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Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data by Baba, Ishaq Abdullahi

“…However, it cannot be applied when the sample size is less than the number of predictor variables. In addressing this problem, some robust procedures for high dimensional dataset via the RFCH algorithm are developed. …”
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Road Sign Detection and Recognition System for Real-Time Embedded Applications by Md Sallah, Siti Sarah, Hussin, Fawnizu Azmadi, Yusoff, Mohd Zuki

“…These variables are compared with the template library which we have developed. …”
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Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers by Uraibi, Hassan S.

“…Hence, Robust Non- Grouped variable selection(RNGVS.RFCH) in the presence of high multicollinearity problem and outliers is developed. …”
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Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio... by Daba, Layth Muwafaq Abdulhussein

“…Unlike the existing optimization algorithm, VL-WIDE features the capability of searching different lengths of solutions to cover the variable number of cloudlets for deployment. …”
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Multiple Linear Regression Models For Estimating True Subsurface Resistivity From Apparent Resistivity Measurements by Bala, Muhammad Sabiu

“…The parameters investigated are apparent resistivity ( a  ), horizontal location (x) and depth (z) as independent variable; while true resistivity ( t  ) is dependent variable.…”
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Classification of tropical rainforest using different classification algorithm based on remote sensing imagery: A study of Gunung Basor by Intan Noradybah Md Rodi

“…Remote sensing technologies are used globally to derive some of crucial spatial variable parameter such as vegetation cover. Three different classification algorithm, minimum distance classifier, Mahalanobis distance classifier and maximum likelihood algorithm was applied to classify the forest area in Gunung Basor. …”
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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

“…Several research efforts have been developed to generate optimal operation rules for dam and reservoir systems utilizing different optimization algorithms. …”
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Predicting sea levels using ML algorithms in selected locations along coastal Malaysia by Hazrin N.A, Chong K.L, Huang Y.F, Ahmed A.N, Ng J.L, Koo C.H, Tan K.W, Sherif M, El-shafie A

“…Data compiled from 1985 to 2018 was utilized for training and testing the developed models. An assessment of the multiple statistics-driven regression algorithms resulted such that each tested location was associated with a particular preferred model. …”

Optimal timber transportation planning in tropical hill forest using bees algorithm by Jamaluddin, Jamhuri

“…The planning depends on the legal restrictions, fixed and variable costs, landing locations, as well as the existing and proposed road network. …”
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Detection of leak size and its location in a water distribution system by using K-NN / Nasereddin Ibrahim Sherksi by Sherksi, Nasereddin Ibrahim

“…Secondly, the data collected from the main valve chamber controllers, which are located in the main pipes. The successfully achieved four set objectives inclusive of (1) a new classification model to detect water leakage, (2) analysis of the effects of leakage size on the variables within a WDS, i.e. flow, pressure, pipe volume, velocity and water demand, (3) locating and specifying the leakage size in the WDS, and (4) evaluate the performance of the designed K-NN algorithm for accurate leak detection. …”
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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

“…The input variables consist of SPM results in modern mathematics, additional mathematics, sciences, physics and English as well as several factors like age, gender, school location and subject stream. …”
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Modification of particle swarm optimization algorithm for optimization of discrete values by Mohd Yassin, Ahmad Ihsan, Jusoh, Muhammad Huzaimy, Abdul Rahman, Farah Yasmin

“…Stochastic optimization algorithms are a new breed of optimizers that have recently been developed. …”
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Linear regression convolutional neural network for fully automated coronary lumen segmentation in intravascular optical coherence tomography / Yong Yan Yin by Yong, Yan Ling

“…In addition, an inter-observer variability test was performed and has shown that the proposed algorithm has comparable variability against manual luminal area estimations by expert human observers. …”
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Development Of Automatic Liver Segmentation Method For Three- Dimensional Computed Tomography Dataset by Chew, Chin Boon

“…The segmentation results from the algorithm developed are competitive. However, improvements still can be made.…”
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Predicting sea levels using ML algorithms in selected locations along coastal Malaysia by Hazrin N.A., Chong K.L., Huang Y.F., Ahmed A.N., Ng J.L., Koo C.H., Tan K.W., Sherif M., El-shafie A.

“…Data compiled from 1985 to 2018 was utilized for training and testing the developed models. An assessment of the multiple statistics-driven regression algorithms resulted such that each tested location was associated with a particular preferred model. …”

Solving the integrated inventory supply chain problems using meta-heuristic methods / Seyed Mohsen Mousavi by Seyed Mohsen , Mousavi

“…First, a novel multi-objective multi-item seasonal inventory control model was developed for known-deterministic variable demands where shortages in combination of backorder and lost sale were considered. …”
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Developing A Prediction Tool To Improve The Shading Efficiency Of The Pedestrian Zones by Khudhayer, Wael A.

“…The shading efficiency represented the percentage of the shaded area to the total floor area of the pedestrian zone, while the targeted shading efficiency indicated the preferable shading requirements for the pedestrian. The development of the prediction tool was conducted base on integrating three sequenced algorithms, which are sun position algorithm, shadow length and position algorithm, and expansion limit algorithm. …”
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Crossover and mutation operators of genetic algorithms by Lim, Siew Mooi, Md. Sultan, Abu Bakar, Sulaiman, Md. Nasir, Mustapha, Aida, Leong, Kuan Yew

“…Genetic algorithms (GA) are stimulated by population genetics and evolution at the population level where crossover and mutation comes from random variables. …”
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