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A comparative study on various ANN optimization algorithms for magnetorheological elastomer carbonyl iron particle concentration estimation
Published 2024“…Therefore, this paper proposed a carbonyl iron particle (CIP) concentration based MRE prediction model using neural network algorithm. …”
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Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization
Published 2022“…The ANN model is further improved using GA and PSO. Each algorithm has its own parameters and is further optimized using RSM. …”
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A concentration prediction-based crop digital twin using nutrient co-existence and composition in regression algorithms
Published 2024“…Crop digital twin is redefining traditional farming practices, offering unprecedented opportunities for real-time monitoring, predictive and simulation analysis, and optimization. This research embarks on an exploration of the synergy between precision agriculture, crop modeling, and regression algorithms to create a digital twin for farmers to augment the concentration and composition prediction-based crop nutrient recovery. …”
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A concentration prediction-based crop digital twin using nutrient co-existence and composition in regression algorithms
Published 2024“…Crop digital twin is redefining traditional farming practices, offering unprecedented opportunities for real-time monitoring, predictive and simulation analysis, and optimization. This research embarks on an exploration of the synergy between precision agriculture, crop modeling, and re-gression algorithms to create a digital twin for farmers to augment the concentration and compo-sition prediction-based crop nutrient recovery. …”
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Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification
Published 2007“…Several simulated systems and real-world timedependent data are used in the investigation. Comparisons based on widely used optimization performance indicators along with outcomes from other research are used. …”
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Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification
Published 2007“…Several simulated systems and real-world timedependent data, are used in the investigation. Comparisons based on widely used optimization performance indicators along with outcomes from other research are used. …”
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Modeling of static and dynamic components of bio-nanorobotic systems
Published 2012“…The first modeling technique applies graph algorithms to compute a new set of optimal weighted structural properties of C60 and C70 fullerenes. …”
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Enhancement of Single and Composite Images Based on Contourlet Transform Approach
Published 2009“…Based on this investigation an optimal color space is selected for both single image and composite image enhancement approaches. …”
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Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…Secondly, this approach hybridizing the FA with the rough algorithm (RA), where RA is used to control the steps of randomness for the FA while optimizing the weights of the standard BPNN model. …”
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An integrated reservoir modelling and evolutionary algorithm for optimizing field development in a mature fractured reservoir
Published 2016“…The second method is automatic optimization using Genetic Algorithm. That depends on the principle of natural selection as proposed by Darwin The genetic program was coupled with the reservoir flow model to re-evaluate the chosen wells at each iteration until obtaining the optimal choice. …”
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Conference or Workshop Item -
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Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification
Published 2007“…Several simulated systems and real-world timedependent data are used in the investigation. Comparisons based on widely used optimization performance indicators along with outcomes from other research are used. …”
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Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool
Published 2019“…This final year project identified relevant parameters through literature research, analysis and expert interview, and evaluated different machine learning algorithms and identified linear regression as the most applicable and efficient with its R-square of 0.8015, qualifying it to be used for the development of a hybrid model for the AI-based tool for predictive process optimization for chemical plants.…”
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Final Year Project -
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Predicting the optimum compositions of a transdermal nanoemulsion system containing an extract of Clinacanthus nutans leaves (L.) for skin antiaging by artificial neural network mo...
Published 2017“…Genetic Algorithm-5-13-1 was found to be the optimum topology for the final model to predict the optimum particle size. …”
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Application of response surface methodology coupled with genetic algorithm in the optimization of cutting conditions for surface roughness in end-milling of Inconel 718 using coate...
Published 2007“…For this purpose, a number of machining experiments based on statistical central composite design of experiments method are carried out. …”
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Proceeding Paper -
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Multivariate Optimization of Biosynthesis of Triethanolamine-Based Esterquat Cationic Surfactant Using Statistical Algorithms
Published 2011“…All process parameters are selected to conduct the optimization by using some statistical algorithms such as Artificial Neural networks (ANNs), Response Surface Methodology (RSM), Wavelet Neural Network (WNN) and Partial Least Squares (PLS). …”
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DEVELOPMENT OF COMPOSITIONAL MODEL FOR PREDICTING VISCOSITY OF CRUDE OILS USING POLYNOMIAL NEURAL NETWORKS (PNN) INDUCED BY GROUP METHOD OF DATA HANDLING (GMDH)
Published 2011“…GMDH is an inductive algorithm for computer-based mathematical modeling using neural network with active neurons that optimizes model coefficients for predetermine mathematical equation and selects the optimal model complexity. …”
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Final Year Project -
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A robust firefly algorithm with backpropagation neural networks for solving hydrogeneration prediction
Published 2018“…For this purpose, the suggested approach that makes a hybridizing the FA with the robust algorithm (RA), where RA is used to control the steps of randomness for the FA while optimizing the weights of the standard BPNN model. …”
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Decentralized Adaptive Pi With Adaptive Interaction Algorithm Of Wastewater Treatment Plant
Published 2014“…The work is highlighted in auto-tuning the PI control parameters in satisfying straighten effluent quality and hence optimizing the nitrogen removal. The Pi controller parameters are obtained by using simple updating algorithm developed based on adaptive interaction theory. …”
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