Search Results - (( basic optimization method algorithm ) OR ( using estimation machine algorithm ))

Parametric coefficient genetic algorithm for domestic water consumption / Nurul Nadia Hani by Hani, Nurul Nadia

“…This research therefore proposes the employment of Genetic Algorithm (GA) to optimize the coefficient of micro-components of water consumption (CMWC) values to determine high influential household routine parameters. …”
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Robust correlation feature selection based support vector machine approach for high dimensional datasets by Baba, Ishaq Abdullahi, Mohammed, Mohammed Bappah, Jillahi, Kamal Bakari, Umar, Aliyu, Hendi, Hasan Talib

“…The third step employs the support vector machine algorithm to calculate prediction values. …”
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Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram by Faris Francis Singaram, Fareena

“…Therefore, this study aimed to used OBIA method with selected machine learning algorithm to estimate the mangrove age by using Sentinel 2A image. …”
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Particle swarm optimization (PSO) for CNC route problem by Nur Azia Azwani, Ismail

“…We often see many of the method of Genetic Algorithm (GA), Ant Colony Optimization (ACO), Simulated Annealing Algorithm (SAA) and PSO are used for any optimization problems. …”
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Processing time estimation in precision machining industry using AI / Lim Say Li by Lim, Say Li

“…Neural Network (NN) model is chosen as the artificial intelligence approach used in this research. Levenberg-Marquardt algorithm is used as the training algorithm. …”
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Estimation of optimal machining control parameters using artificial bee colony by Norfadzlan, Yusup, Arezoo, Sarkheyli, Azlan, Mohd Zain, Siti Zaiton, Mohd Hashim, Norafida, Ithnin

“…Five machining control parameters that are optimized using ABC algorithm include traverse speed (V), waterjet pressure (P), standoff distance (h), abrasive grit size (d) and abrasive flow rate (m). …”
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Machine Learning Regression Approach for Estimating Energy Consumption of Appliances in Smart Home by Husin N.S.I.M., Mostafa S.A., Jaber M.M., Gunasekaran S.S., Al-Shakarchi A.H., Abdulsattar N.F.

“…This paper attempts to use machine learning algorithms to estimate the energy consumption of appliances in a smart home environment. …”

Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

“…Meanwhile, the proposed QOJaya algorithm produces better results than the basic Jaya method in terms of solution optimality and convergence speed. …”
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Estimating Depressive Tendencies Of Twitter User Via Social Media Data by Loh, Hooi Teng

“…We will use these three machine learning algorithms to compare the accuracy and performance of the depressed twitter user. …”
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Software project estimation with machine learning by Zakaria, Noor Azura, Ismail, Amelia Ritahani, Yakath Ali, Afrujaan, Mohd Khalid, Nur Hidayah, Zainal Abidin, Nadzurah

“…This project involves research about software effort estimation using machine learning algorithms. Software cost and effort estimation are crucial parts of software project development. …”
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Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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Assessment of forest aboveground biomass estimation from superview-1 satellite image using machine learning approaches / Azinuddin Mohd Asri by Mohd Asri, Azinuddin

“…In contrast, machine learning is used to calculate the accuracy assessment of dependent between independent variables. …”
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Extreme learning machine model for state-of-charge estimation of lithium-ion battery using gravitational search algorithm by Hossain Lipu M.S., Hannan M.A., Hussain A., Saad M.H., Ayob A., Uddin M.N.

Software effort estimation using machine learning technique by Rahman, Mizanur, Roy, Partha Protim, Ali, Mohammad, Gonçalves, Teresa, Sarwar, Hasan

“…In order to better effectively evaluate predictions, this study recommends various machine learning algorithms for estimating, including k-nearest neighbor regression, support vector regression, and decision trees. …”
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Data Analysis using Particle Swarm Optimization Algorithm by Tai, Zu Jie

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Using Electromagnetism-like algorithm and genetic algorithm to optimize time of task scheduling for dual manipulators by Abed I.A., Sahari K.S.M., Koh S.P., Tiong S.K., Jagadeesh P.

“…A method based on Electromagnetism-Like algorithm (EM) and Genetic Algorithm (GA) is proposed to determine the time-optimal task scheduling for dual robot manipulators. …”

Stator resistance estimation of induction motor using genetic algorithm by Nurul Syamila, Mohd Rosli

“…This project is about to design genetic algorithm estimator using MATLAB software, and builds an actual induction motor using Newcastle University Drives Simulation Library. …”
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Sensorless control system for assistive robotic ankle-foot by Al Kouzbary, Mouaz, Abu Osman, Noor Azuan, Wahab, Ahmad Khairi Abdul

“…Both estimation algorithms are built using C-code and assessed in MATLAB Simulink. …”
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Estimation of electric vehicle turning radius through machine learning for roundabout cornering by Ashaa, Supramaniam, Muhammad Aizzat, Zakaria, Kunjunni, Baarath, Mohamad Heerwan, Peeie, Ahmad Fakhri, Ab. Nasir, Muhammad Izhar, Ishak

“…This paper presents an alternative approach for estimating the turning radius using machine learning technique. …”
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Pelvic classification based on deep learning algorithm on clinical CT scans in Malaysian population by Yahaya, Yasmin Arijah Che

“…For samples under 20 years old, the precision, sensitivity and specificity cannot be calculated as the result by Google Teachable Machine is error. This research concludes that using Google Teachable Machine provide high accuracy and precision for sex estimation but not useful for age classification for sample below 20 years old.…”
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