Search Results - (( developing waste maximization algorithm ) OR ( java visualization learning algorithm ))

Development Of Machine Learning User Interface For Pump Diagnostics by Lee, Zhao Yang

“…Build up a user interface by using Visual Studio Code (VSC) to run the coding of Cascading Style Sheet (CSS), Hyper Text Markup Language (HTML) and JavaScript (JS) as a webpage and connect to Azure Machine Learning Model and this will allow the user from using the model from a webpage when they have active internet with any devices.…”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform by Alias, Norma, Satam, Noriza, Abd. Ghaffar, Zarith Safiza, Darwis, Roziha, Hamzah, Norhafiza, Islam, Md. Rajibul

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Mobile application for real time baby sign language recognition using YOLOv8 / Siti Aishah Idris and Ahmad Firdaus Ahmad Fadzil by Idris, Siti Aishah, Ahmad Fadzil, Ahmad Firdaus

“…The model will be designed and developed using a deep learning algorithm, which is YOLOv8, the latest version of YOLO. …”
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Spatial Data Mining Model For Landfill Sites Suitability Mapping Based On Neural Networks And Multivariate Analysis by Abujayyab, Sohaib K. M.

“…It is very crucial to have a precise suitability mapping workflow for new landfill sites in the development planning of municipal solid waste management systems. …”
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Controlling Algorithm for Energy-Consumption, Radio Bandwidth and Signal Strength Deploying Single Fitness Function to Solve Coverage Area Problems by Marsal, Kalid Abdlkader, Abdullah, Ismail, Waidah Ismail, Khairi Abdul Rahim

Optimizing strength of directly recycled aluminum chip-based parts through a hybrid RSM-GA-ANN approach in sustainable hot forging by M. Altharan, Yahya, Shamsudin, Shazarel, Lajis, Mohd Amri, Al-Alim, Sami, Yusuf, Nur Kamilah, Mohammed Alduais, Nayef Abdulwahab, M. Ghaleb, Atef, Zhou, Wenbin

“…This work was carried out to study the application of hot press forging (HPF) in recycling AA6061 aluminum chip waste, aiming to optimize operating factors using Response Surface Methodology (RSM), Artificial Neural Network (ANN) and Genetic algorithm (GA) strategy to maximize the strength of recycled parts. …”
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Optimizing strength of directly recycled aluminum chip-based parts through a hybrid RSM-GA-ANN approach in sustainable hot forging by M. Altharan, Yahya, Shamsudin, Shazarel, Lajis, Mohd Amri, Al-Alimi, Sami, Yusuf, Nur Kamilah, M. Ghaleb, Atef, Zhou, Wenbin

“…This work was carried out to study the application of hot press forging (HPF) in recycling AA6061 aluminum chip waste, aiming to optimize operating factors using Response Surface Methodology (RSM), Artificial Neural Network (ANN) and Genetic algorithm (GA) strategy to maximize the strength of recycled parts. …”
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Optimizing strength of directly recycled aluminum chip-based parts through a hybrid RSM-GA-ANN approach in sustainable hot forging by M. Altharan, Yahya, Shamsudin, Shazarel, Lajis, Mohd Amri, Sami Al-Alimi, Sami Al-Alimi, Yusuf, Nur Kamilah Y, Mohammed Alduais, Nayef Abdulwahab, Atef M. Ghaleb, Atef M. Ghaleb, Wenbin Zhou, Wenbin Zhou

“…This work was carried out to study the application of hot press forging (HPF) in recycling AA6061 aluminum chip waste, aiming to optimize operating factors using Response Surface Methodology (RSM), Artificial Neural Network (ANN) and Genetic algorithm (GA) strategy to maximize the strength of recycled parts. …”
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Single fitness function analysis of energy-consumption and radio bandwidth management in coverage area problems by Kalid Abdlkader Marsal

Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network by Mohamad Afiq, Mohd Asrul

“…The review of optimization studies in the literature contributes to the development of a flowchart of an advanced optimization strategy that serves as a guide for the methodology of the study. …”
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Graphical user interface test case generation for android apps using Q-learning / Husam N. S. Yasin by Husam , N. S. Yasin

“…Hence, it proposes a Q-Learning-based test coverage approach developed in DroidbotX to generate GUI test cases for Android apps. …”
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