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Grouper fish feed formulation using enhanced evolutionary algorithm with fibonacci rabbit initialization and binary-standard deviation tournament selection by Soong, Cai Juan

“…Therefore, this research focused on feed formulation for grouper fish taking into consideration suitable 14 ingredients and 15 nutrients. …”
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A multi-criteria proximal bundle-based optimization approach to chick-mash feed formulation by Abayomi, Olalere Olusegun, Ruth, Alara Oluwaseun, Bala, Mohamed Saad, Twibi, Mohamed Farag

“…The development of feed formulation is essentially a problem of optimization which involves selecting the best alternative, starting from a specified set of possibilities. …”
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An Evolutionary Algorithm: An Enhancement of Binary Tournament Selection for Fish Feed Formulation by Soong, Cai Juan, Abd Rahman, Rosshairy, Ramli, Razamin, Abd Manaf, Mohammed Suhaimee, Chek-Choon, Ting

“…*e proposed selection operator has been experimented within fish feed formulation in grouper fish farming as a case study on finding the minimum cost and fulfilling constraints. …”
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Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

“…In conclusion, a deep reinforcement learning algorithm was successfully developed for the substrate feeding rate optimisation in the fed-batch baker’s yeast fermentation process. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Development of deep reinforcement learning based resource allocation techniques in cloud radio access network by Amjad, Iqbal

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A pond-surface-based Biofloc-farm health-monitoring system for African catfish using deep learning methods by Nizam Nordin

“…The research methodology stages are; (i) Acquisition of daily recordings of the surfaces of fish ponds and their respective daily health, (ii)Formulating and developing a fish health monitoring algorithm based on their behaviour from the surface, (iii) Selection of training data based on the recordings and health,(iv) performance metric evaluation, (v) Assessment of experimental results of the Biofloc Fish Health Monitoring System On Pond Surface algorithm, and (vi) final report and project wrap-up. …”
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Development of tool life prediction model of TiAlN coated tools during the high speed hard milling of AISI H13 steel by Amin, A. K. M. Nurul, Hafiz, A.M. Khalid, Lajis, M. A.

“…In current study, the model has been developed by RSM in terms of cutting speed (v), feed (f) and axial depth of cut (a). …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Modeling and sensitivity analysis of a multi-nets anns model for real-time performance-based condition monitoring of an industrial gas turbine engine by Tahan, M., Sarwar, U., Muhammad, M., Abdul Karim, Z.A.

“…Three-layer feed-forward configuaration is chosen to construct the networks, the Levenberg-Marquardt algorithm is used as the training function, and the k-fold cross-validation process is employed to obtain the optimum number of neurons in the hidden layers. …”
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Modeling and sensitivity analysis of a multi-nets anns model for real-time performance-based condition monitoring of an industrial gas turbine engine by Tahan, M., Sarwar, U., Muhammad, M., Abdul Karim, Z.A.

“…Three-layer feed-forward configuaration is chosen to construct the networks, the Levenberg-Marquardt algorithm is used as the training function, and the k-fold cross-validation process is employed to obtain the optimum number of neurons in the hidden layers. …”
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Comparative modelling of strength properties of hydrated-lime activated rice husk-ash (HARHA) modified soft soil for pavement construction purposes by artificial neural network (AN... by Onyelowe, K. C., Alaneme, G. U., Onyia, M. E., Bui Van, D., Dimonyeka, M. U., Nnadi, E., Ogbonna, C., Odum, L. O., Aju, D. E., Abel, C., Udousoro, I. M., Onukwugha, E.

“…For the ANN model, feed forward back propagation and Levernberg Marquardt training algorithm were utilized for the model development with the optimized network architecture of 8-6-3 derived based on MSE performance criteria; while for the fuzzy logic model, the mamdani FIS with both triangular and trapezoidal membership function with both models formulated, simulated and computed using MATLAB toolbox. …”
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Neural network based adaptive pid controller for shell-and-tube heat exchanger by Othman, Mohamad Hakimi

“…Dynamic time series neural network model was used together with Levenberg-Marquardt algorithm as the training method. Single hidden layer feed forward neural networks with 20 neurons in hidden layer was selected. …”
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Neural network based adaptive pid controller for shell-and-tube heat exchanger: article by Othman, Mohamad Hakimi

“…Dynamic time series neural network model was used together with Levenberg-Marquardt algorithm as the training method. Single hidden layer feed forward neural networks with 20 neurons in hidden layer was selected. …”
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The predictive machine learning model of a hydrated inverse vulcanized copolymer for effective mercury sequestration from wastewater by Ghumman, A.S.M., Shamsuddin, R., Abbasi, A., Ahmad, M., Yoshida, Y., Sami, A., Almohamadi, H.

“…NMDG functionalized IVP removed 100 Hg2+ from a low feed concentration (10â��50 mg/l). A predictive machine learning model was also developed to predict the amount of mercury removed () using GPR, ANN, Decision Tree, and SVM algorithms. …”
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Optimization of hydropower reservoir system using genetic algorithm for various climatic scenarios by Tayebiyan, Aida

“…The developed models have been applied to the Cameron Highland and Batang Padang Hydro Scheme (CHBPHS) in Cameron Highland, Malaysia. …”
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Improvement of xylanase production by recombinant Escherichia coli DH5α using fed-batch fermentation by Basar, Bazilah

“…Constant and exponential fed-batch fermentations were carried out using 2 L stirred tank fermenter equipped with Multi Fermenter Control System (MFCS) to control the feeding rate of feeding medium into the culture according to the proposed algorithm. …”
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