Search Results - (( waste interaction model algorithm ) OR ( java implication based algorithm ))

The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Bayesian optimized multilayer perceptron neural network modelling of biochar and syngas production from pyrolysis of biomass-derived wastes by Kanthasamy, R., Almatrafi, E., Ali, I., Hussain Sait, H., Zwawi, M., Abnisa, F., Choe Peng, L., Victor Ayodele, B.

“…This study employs Bayesian optimized multilayer perceptron neural network for modelling the prediction of biochar and syngas from pyrolysis of biomass-derived wastes. …”
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Production and characterization of biochar derived from oil palm wastes, and optimization for zinc adsorption by Zamani, Seyed Ali

“…The incremental back propagation algorithm demonstrated the best results and which has been used as learning algorithm for ANN in combination with Genetic Algorithm in the optimization. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

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

“…The experimental runs were designed using Full factorial and RSM via Minitab 21 software. RSM-ANN models were employed to examine the effect of factors and their interactions on response and to predict output, while GA-RSM and GA-ANN were used for optimization. …”
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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

“…The experimental runs were designed using Full factorial and RSM via Minitab 21 software. RSM-ANN models were employed to examine the effect of factors and their interactions on response and to predict output, while GA-RSM and GA-ANN were used for optimization. …”
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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

“…The experimental runs were designed using Full factorial and RSM via Minitab 21 software. RSM-ANN models were employed to examine the effect of factors and their interactions on response and to predict output, while GA-RSM and GA-ANN were used for optimization. …”
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Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network by Mohamad Afiq, Mohd Asrul

“…Model validity describes the first sub-objective, which is to solve the complexity of the nonlinear interaction of multiple MEC input variables related to the hydrogen production rate response using artificial neural networks (ANN) before validating the mathematical modeling results by comparing experimental data with the predicted substrate concentration profile and hydrogen production rate profile based on the re-estimated input values of the model parameters using single-objective optimization based on the nonlinear convex method using gradient descent algorithm. …”
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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

“…Exploring the app's state extensively requires long event sequences to find the correct combination of actions, leading to excessively long transitions and wasted time. Such tools must choose not only which user interface element to interact with, but also which type of action to be performed to increase the percentage of code coverage and to detect faults with a limited time budget. …”
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