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Improved whale optimization algorithm for feature selection in Arabic sentiment analysis by Tubishat, Mohammad, Abushariah, Mohammad A.M., Idris, Norisma, Aljarah, Ibrahim

“…In SA, feature selection phase is an important phase for machine learning classifiers specifically when the datasets used in training is huge. Whale Optimization Algorithm (WOA) is one of the recent metaheuristic optimization algorithm that mimics the whale hunting mechanism. …”
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Time series predictive analysis based on hybridization of meta-heuristic algorithms by Mustaffa, Zuriani, Sulaiman, Mohd Herwan, Rohidin, Dede, Ernawan, Ferda, Kasim, Shahreen

“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

“…Alan Fan et aI., [2] use Support Vector Machine (SVM) to stock market prediction. The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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Time series predictive analysis based on hybridization of meta-heuristic algorithms by Zuriani, Mustaffa, M. H., Sulaiman, Rohidin, Dede, Ernawan, Ferda, Shahreen, Kasim

“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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Fuzzy logic-based arrival time estimation for indoor navigation using augmented reality by Mohammed Sohif, Muhammad Hidayat, Mardzuki, Muhammad Imran, Mohd Ibrahim, Azhar, Haja Mohideen, Ahmad Jazlan

“…This study proposes a mobile AR application for indoor navigation that uses an intelligent signage algorithm based on fuzzy logic to estimate arrival time. …”
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Expectation maximization clustering algorithm for user modeling in web usage mining system by Mustapha, Norwati, Jalali, Manijeh, Jalali, Mehrdad

“…In this study we advance a model for mining of user’s navigation pattern. The model is based on expectation-maximization (EM) algorithm and it is used for finding maximum likelihood estimates of parameters in probabilistic models, where the model depends on unobserved latent variables. …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

“…Finally, rule-based optimisation techniques such as Particle Swarm Optimization (PSO), Differential Evolution (DE) and Grey Wolf Optimizer (GWO) were used to minimise the amount of time employed in the stock market turning points prediction. …”
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Improvement of an integrated global positioning system and inertial navigation system for land navigation application by Hasan, Ahmed Mudheher

“…The proposed hybrid method is simple, easy to implement and can be used to automate the INS-error estimation step used in the proposed integrated GPS/INS navigator. …”
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Automatic estimation of inertial navigation system errors for global positioning system outage recovery by Hasan, Ahmed Mudheher, Samsudin, Khairulmizam, Ramli, Abdul Rahman, Raja Abdullah, Raja Syamsul Azmir

“…Kalman filter (KF) is widely used in INS and GPS integration to present a forceful navigation solution by overcoming the GPS outage problems. …”
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Development of a motion planning and obstacle avoidance algorithm using adaptive neuro fuzzy inference system for mobile robot navigation by Muslim, Farah Kamil Abid

“…Finally, the last objective is to improve the optimality of the new approach using a robust Machine Learning strategy. An adaptive neuro-fuzzy inference system (ANFIS) was designed which constructs and optimizes a fuzzy logic controller using a given dataset of input/output variables in order for the mobile robot to learn. …”
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Collision Free Control of Variable Length Hyper Redundant Robot Manipulator by Annisa, Jamali, M. Raisuddin, Khan, M. Shahril, Osman, M. Mozasser, Rahman, Muhamad Fadzli, Ashari, Mohd Syahmi, Jamaludin, Ervina, Junaidi

“…Hyper-redundant robot (HRR) manipulators are useful at navigating convoluted paths, but conventionally complicated to control. …”
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Collision free control of variable length hyper redundant robot manipulator by Jamali, Annisa, Khan, Md. Raisuddin, Osman, M. Shahril, Rahman, Md. Mozasser, Ashari, Muhd Fadzli, Jamaludin, Mohd Syahmi, Junaidi, Ervina

“…Hyper-redundant robot (HRR) manipulators are useful at navigating convoluted paths, but conventionally complicated to control. …”
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A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

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Artificial neural network modelling of photodegradation in suspension of manganese doped zinc oxide nanoparticles under visible-light irradiation by Abdollahi, Yadollah, Zakaria, Azmi, Sairi, Nor Asrina, Matori, Khamirul Amin, Masoumi, Hamid Reza Fard, Sadrolhosseini, Amir Reza, Jahangirian, Hossein

“…Therefore, QP-4-8-1 was selected as final model for validation test and navigation of the process. The model was used for determination of the optimum values of the effective variables by a few three-dimensional plots. …”
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Optimal Reactive Power Dispatch Solution by Loss Minimization Using Moth-Flame Optimization Technique by Rebecca Ng, Shin Mei, Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Hamdan, Daniyal

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Multi-Objective Multi-Exemplar Particle Swarm Optimization Algorithm with Local Awareness by Noori, Mustafa Sabah, Sahbudin, Ratna K.Z., Sali, Aduwati, Hashim, Fazirulhisyam

“…Multi-Objective Optimization (MOO) algorithms play a crucial role in this process by enabling them to navigate these trade-offs effectively. …”
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Development of a two-level trade credit model with shortage for deteriorating products using hybrid metaheuristic algorithm by Molamohamadi, Zohreh

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Obstacle avoidance robot using sonar sensor (OARuS) by Mohamad Sabri Abdullah

“…I choose this type of sensor is because it can send and receive signal only using one sensor. After I test these sensors, I choose to use an LV-MaxSonar@EZ1 as my transducer because these sensors have more advantage such as easy to use, range stability, continuously variable gain, quality beam shape, wave form analysis, calibration and test, very small size (and weight), low cost, low power, and wide operating voltage for this system. …”
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Scheduling the blended solution as industrial CO2 absorber in separation process by back-propagation artificial neural networks by Abdollahi, Yadollah, Sairi, Nor Asrina, Mohd Said, Suhana, Abouzari-lotf, Ebrahim, Zakaria, Azmi, Mohd Sabri, Mohd Faizul, Islam, Aminul, Alias, Yatimah

“…Therefore, the blend’s components and operating temperature were modeled and optimized as input effective variables to minimize its viscosity as the final output by using back-propagation artificial neural network (ANN). …”
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Simultaneous measurement of multiple soil properties through proximal sensor data fusion: a case study by Wenjun, Ji, Adamchuk, Viacheslav I., Song, Chao Chen, Mat Su, Ahmad S., Ismail, Ashraf, Qianjun, Gan, Zhou, Shi, Biswas, Asim

“…Predictions of pH and LBC were only feasible using MARS and PLSR, respectively. In this field, it was not possible to predict extractable P and K using all tested sensor combinations or algorithms. …”
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