AI-driven nonlinear optimization for knowledge extraction and pattern analysis in IoT-enabled data mining systems by Alimjon, Dadamuxamedov

“…The paper explains the complexity and heterogeneity of IoT data on scale by declaring and resolving nonlinear optimization problems using the latest AI methods, including genetic algorithms and neural networks. …”
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Gene Selection for Microarray Data Classification based on Grey Wolf Optimizer Enhanced with TRIZ-inspired Operators by Abou Doush, Iyad

“…Pattern recognition algorithms are widely applied to gene expression data to differentiate between health and cancerous patient samples. …”
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A hybrid of clustering and meta-heuristic algorithms to solve a p-mobile hub location–allocation problem with the depreciation cost of hub facilities by Mahdi Mokhtarzadeh (11593310)

“…To solve the proposed model, four meta-heuristic algorithms, namely multi-objective particle swarm optimization (MOPSO), a non-dominated sorting genetic algorithm (NSGA-II), a hybrid of k-medoids as a famous clustering algorithm and NSGA-II (KNSGA-II), and a hybrid of K-medoids and MOPSO (KMOPSO) are implemented. …”

Intelligent route to design efficient CO₂ reduction electrocatalysts using ANFIS optimized by GA and PSO by Majedeh Gheytanzadeh (17541927)

“…The primary purpose of this study is to establish a new model through machine learning methods; namely, adaptive neuro-fuzzy inference system (ANFIS) combined with particle swarm optimization (PSO) and genetic algorithm (GA) for the prediction of *CO (the key intermediate) adsorption energy as the efficiency metric. …”

The survey of cluster based data collection process for iot enabled wireless sensor network using several optimization technique by Abirami, R.

“…The study analyses nature-based metaheuristic methods such as the Genetic Algorithms, Particle Swarm Optimization, Firefly Optimization, Gray Wolf Optimization and Water-Cycle Algorithms, and specialised protocols of clustering, routing and data aggregation. …”
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A Biologicaly Inspired Decision Model for Multivariable Genetic- Fuzzy-AHP System by Kouatli, Issam

“…This paper describes a hybridized intelligent algorithm as a tuning mechanism for one type of Genetic Fuzzy system termed the Genetic Fuzzimetric Technique (GFT). …”
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Definition and selection of fuzzy sets in genetic‐fuzzy systems using the concept of fuzzimetric arcs by Kouatli, Issam

“…An irregular shape may be required by some systems. Hence, a genetic algorithm was proposed as a methodology to optimize the performance of fuzzy systems by mutating different regular shapes. …”
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Dynamic performance evaluation and machine learning-assisted optimization of a solar-driven system integrated with PCM-based thermal energy storage: A case study approach by Haitham Osman (11737057)

“…A comprehensive techno-economic analysis is conducted, supported by a machine learning-assisted optimization framework that combines artificial neural networks with genetic algorithms. …”

Student advising decision to predict student's future GPA based on Genetic Fuzzimetric Technique (GFT) by Kouatli, Issam

“…Looking at the historical data of students, fuzzy logic can be used to develop rules based on these data. Genetic Algorithm would be used to optimize the performance of the system.…”
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A Literature Review on System Dynamics Modeling for Sustainable Management of Water Supply and Demand by Khawar Naeem (17984062)

“…The models included agent-based modeling (ABM), Bayesian networking (BN), analytical hierarchy approach (AHP), and simulation optimization multi-objective optimization (MOO). The solution approaches included the genetic algorithm (GA), particle swarm optimization (PSO), and the non-dominated sorting genetic algorithm (NSGA-II). …”

Software defect prediction. (c2019) by Moussa, Rebecca

“…One that focuses on predicting defect in software modules using a hybrid heuristic - a combination of Particle Swarm Optimization (PSO) and Genetic Algorithms (GA). We compare our approach to 9 well known machine learning techniques and results show the advantages of our model over the other techniques. …”
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Cost-Benefit Analysis of Genotype-Guided Interruption Days in Warfarin Pre-Procedural Management by Islam, Eljilany

“…As per 10.3% prevalence of genetic variants, 82% bridging, and a calculated 20% optimization in the preparative period of warfarin management, the benefit to cost ratio was 4.0 in favor genotype-guided approach. …”
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A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti (21593819)

“…<p dir="ltr">Autism Spectrum Disorder (ASD) is a genetic and neurological condition that leads to difficulties in communication and social interaction. …”

Power system output feedback stabilizer design via geneticalgorithms by Abdel-Magid, Y.L.

“…In the second method, the problem of selecting the output feedback gains is converted to a simple optimization problem with an eigenvalue based objective function, which is solved by a genetic algorithm. …”
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Digital circuit design through simulated evolution (SimE) by Sait, Sadiq M.

“…Area, power and delay are considered in the optimization of circuits. Results obtained by SimE algorithm are compared to those obtained by genetic algorithm (GA).…”
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Implementation of a Multivariable Modular Structure for Fuzzy Taxi Scheduling System (FTSS) by Kouatli, Issam

“…Fuzzy logic can be utilized to deal with such uncertainty in the information. Genetic algorithm can be utilized for optimization of solution. …”
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Development and Implementation of a Hybrid Intelligent Controller for Interior Permanent Magnet Synchronous Motor Drives by Nasir Uddin, M.

“…At each operating condition a genetic algorithm is used to optimize the PI controller parameters in a closed-loop vector control scheme. …”
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Simulated evolution for timing and low power VLSI standard cell placement by Sait, Sadiq M.

“…For this hard multiobjective combinatorial optimization problem, no known exact and efficient algorithms exist that guarantee finding a solution of specific or desirable quality. …”
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Final exams scheduling for univeristies. (c2001) by Timany, Mazen Nuhad

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Complexity Avoidance using Biological Resemblance of Modular Multivariable Structure by Kouatli, Issam

“…GFT (Genetic Fuzzimetric Technique) is of no exception which merges Fuzzy logic with genetic algorithm to achieve the optimization of the decision making process under uncertainty. …”
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