Predicting insulin dosage for diabetic patients to reach optimal glucose levels. (c2012) by Bitar, Mandy

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AI-Based Methods for Predicting Required Insulin Doses for Diabetic Patients by Azar, Danielle

“…Hence, there is a great need to automate this process. In this paper, we propose and compare three techniques two of which are Artificial Intelligence techniques, namely C4.5 and Case-Based Reasoning, and the third one is a meta-heuristic namely genetic algorithms. …”
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DSCE: Comparative Analysis of Heuristic Computational Techniques by Bany Muhammad, Nooh

“…Various HCTs are also compared, including genetic algorithms (GAs), particle swarm optimization (PSO), differential evolution (DE), cat swarm optimization (CSO), bee colony optimization (BCO), hybrid GA-PSO (HGP), and the cuckoo search algorithm (CSA). …”
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Improving Rule Set Based Software Quality Prediction by Azar, Danielle

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Scheduling and allocation in high-level synthesis using stochastic techniques by Sait, Sadiq M.

“…Scheduling and allocation can be formulated as an optimization problem. In this work, a unique approach to scheduling and allocation problem using the genetic algorithm (GA) is described. …”
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Dynamic single node failure recovery in distributed storage systems by Itani, M.

“…We selected fractional repetition coding due to its simple repair mechanism that minimizes the repair and disk access bandwidths together with the property of un-coded repair process. To minimize the system repair cost, we formulate our problem using incidence matrices and solve it heuristically using genetic algorithms for all possible cases of single node failures. …”
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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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Tuning of AGC of interconnected reheat thermal systems with geneticalgorithms by Abdel-Magid, Y.L.

“…A digital simulation is used in conjunction with the genetic algorithm optimization process. …”
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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. …”

Software tool for regression testing. (c1997) by Araby, Nidal H.

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Inferential sensing techniques in industrial applications by Shakil,, Muhammad

“…System delays are obtained by approximating the model by a linear model. Genetic algorithm, which is a heuristic optimization technique, is used to ¯nd the system delays of the linear model, which are used in dynamical neural network model. …”
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Pre-production movie rating prediction using machine learning. (c2017) by Gerges, Firas Abdallah

“…In this work, we present several machine learning techniques (Support Vectors Machine, K-Nearest Neighbors, C5, Neural Networks and Case-Based Reasoning) along with a genetic algorithm to predict the success of a movie before its production using the IMDB rating as an indicator of the success. …”
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Using artificial bee colony to optimize software quality estimation models. (c2015) by Abou Assi, Tatiana Antoine

“…In order to measure such software quality characteristics, we must wait until the software is implemented, tested and put to use for a certain amount of time. Several software metrics have been proposed in the literature to avoid this long and costly process, and they proved to be a good means of estimating software quality. …”
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Energy removal in dynamical systems through an optimal sequence of constraint application by Issa, Jimmy

“…In this paper several optimization formulations are suggested, whereby maximum energy removal is achieved by selecting optimal strategies that identify where and when the constraints should be applied. The optimization process is illustrated by means of simple mass-spring and membrane systems and the corresponding problems are solved using a genetic algorithm.…”
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Reliability and fault tolerance based topological optimization of computer networks - part II: iterative techniques by Abd-El-Barr, Mostafa

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Improving passenger satisfaction at Kuwait International Airport by using multi-objective optimisation by Alsaber, Ahmad

“…The proposed methods employ optimisation techniques such as mixed integer goal programming (MIGP) and genetic algorithm (GA) to offer a comparative multi-solution outcome towards optimising the passenger quality of services at airport departure check-in. …”
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Recent advances on artificial intelligence and learning techniques in cognitive radio networks by Abbas, Nadine

“…The literature survey is organized based on different artificial intelligence techniques such as fuzzy logic, genetic algorithms, neural networks, game theory, reinforcement learning, support vector machine, case-based reasoning, entropy, Bayesian, Markov model, multi-agent systems, and artificial bee colony algorithm. …”
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