Search Results - (( model relationships _ algorithm ) OR ( rate optimization based 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 objective of this research is to develop and compare various ANN spray drying coconut milk models. Firstly, using MATLAB program, the ANN model is developed based on optimized topology and is then furthered optimized by genetic algorithm (GA) and particle swarm optimization (PSO) using MINITAB program. …”
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2
Ant colony optimization and genetic algorithm models for suspended sediment discharge estimation for gorgan-river, Iran
Published 2011“…Therefore, it is still necessary to develop the model for the discharge-sediment relationship. New models based on artificial intelligence models, namely; Ant Colony Optimization (ACO) and Genetic Algorithm (GA) are now being used more frequently to solve optimization problems. …”
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3
Automatic control of flotation process using computer vision
Published 2015“…The performance of improved marker based watershed algorithm was validated by using several industrial and laboratory froth images. …”
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4
Multivariate Optimization of Biosynthesis of Triethanolamine-Based Esterquat Cationic Surfactant Using Statistical Algorithms
Published 2011“…In this work, triethanolamine and oleic acid were chosen as substrates to design an optimal model reaction which will lead to high conversion rate utilizing lipase from Candida antacrctica (Novozyme 435) as biocatalyst in the organic solvent system. …”
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5
Experimental Investigation and Optimization of Minimum Quantity Lubrication for Machining of AA6061-T6
Published 2015“…Process parameters including the cutting speed, depth of cut, feed rate and MQL flow rate are selected for study to develop an optimization model for flank wear based on the genetic algorithm. …”
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Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar
Published 2019“…In this study, the performance of these three algorithms in obtaining the optimal blade design based on the �436�45D are investigated and compared. …”
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7
Development of a hybrid PSO-ANN model for estimating glucose and xylose yields for microwave-assisted pretreatment and the enzymatic hydrolysis of lignocellulosic biomass
Published 2018“…ANN is a powerful tool capable of determining the relationship between the desired input and output data while PSO was used as a robust population-based search algorithm to optimize the performance of the ANN model. …”
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Dynamic Economic Dispatch For Large Scale Power Systems: A Lagrangian Relaxation Approach
Published 1991“…The solution algorithm is based on Lagrangian relaxation and on exploiting the intimate relationship between optimizing the dual Lagrangian function and Dantzig-Wolfe decomposition. …”
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Biochar production from valorization of agricultural Wastes: Data-Driven modelling using Machine learning algorithms
Published 2023“…The artificial neural network-based algorithms outperformed the SVM and GPR as indicated by the R2 > 0.9 and low predictive errors. …”
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10
Rank-based optimal neural network architecture for dissolved oxygen prediction in a 200L bioreactor
Published 2017“…In a fermentation process, dissolved oxygen (DO) concentration is mostly affected by aeration rate, and agitation speed and temperature. Thus it is beneficial to model the relationship of DO concentration with these variables based on real process data for further use in controller design. …”
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Fuzzy-Genetic based approach in decision making for repair of turbochargers using additive manufacturing
Published 2023“…Genetic algorithm optimization method was used to optimize the cost of the repairing process once the decision on whether the turbocharger was repairable was determined by the Fuzzy system. …”
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Leveraging transfer learning and label optimization for enhanced traditional Chinese medicine ner performance
Published 2024“…To address label-related issues in the baseline model, a scheme was proposed to improve the learning rate of the CRF layer, resulting in an increased F1 measure of 91.0%. …”
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Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…A new meta-heuristic optimization technique called the Slime Mould Algorithm (SMA) approach has a high convergence rate or a few iterations and superior optimization indices analyzed against other algorithms. …”
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15
A novel ensemble decision tree-based CHi-squared Automatic Interaction Detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping
Published 2014“…An ensemble algorithm of data mining decision tree (DT)-based CHi-squared Automatic Interaction Detection (CHAID) is widely used for prediction analysis in variety of applications. …”
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Driver behaviour classification: a research using OBD-II data and machine learning
Published 2024“…Then, the proposed model makes use of the K-Means algorithm to create driving behaviour labels whether belong to safe or aggressive - validated by the safety score criteria. …”
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An enhanced opposition-based firefly algorithm for solving complex optimization problems
Published 2014“…Firefl y algorithm is one of the heuristic optimization algorithms which mainly based on the light intensity and the attractiveness of fi refl y. …”
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Machining optimization using Firefly Algorithm / Farhan Md Jasni
Published 2020“…Based on the previous research on the success of Firefly Algorithm, this approach will be able to optimize the machining parameter of milling operation. …”
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Student Project -
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Enhancing three variants of harmony search algorithm for continuous optimization problems
Published 2021“…Meta-heuristic algorithms are well-known optimization methods, for solving real-world optimization problems. …”
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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance
Published 2020“…Experimentally, the PMT shows promising results by accelerating the convergence rate against the original algorithms with the same number of fitness evaluations comparing to the original metaheuristic algorithms in benchmark functions and real-world optimization problems.…”
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Thesis
