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104 articles for “Genetic Algorithms”
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Research ArticleOpen accessIn the abstractConstrained Modified Genetic Algorithm for Optimizing RICE Climate Change Model PolicyHaitham OsmanThe objective of this paper is to use evolutionary algorithm for policy making to help in decision support, the Regional Integrated Climate-Economy (RICE) model for the dynamic climate change is used to optimize the tradeoff policy between abating of carbon dioxide emissions to reduce global climate change and in the other hand the resulting in economic damages. A Constrained Genetic … …American Journal of Applied Sciences, Vol. 14, Issue 10 · 12 Apr 2017 · 7,512 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybrid Clustering Process using a Genetic Fuzzy System for the Knowledge Base of a Fuzzy Rule-Based SystemHamedoun Lamiae, Attariuas Hicham, Ben Maati Mohamed LarbiThe present paper proposes a new Hybrid clustering Process based on Fuzzy Genetic System. The proposed Approach consists of two steps: (1) Using a method called Fuzzy clustering, all data elements will be clustered into N groups; (2) utilizing a Fuzzy Genetic System, for every level the fuzzy rule of adhesion will be generated. If we compare our research to … …Journal of Computer Science, Vol. 12, Issue 12 · 6 Feb 2017 · 6,647 accessesView PDFCite
Research ArticleOpen accessIn the abstractEchocardiographic Pulmonary to Left Atrial Ratio in Dogs (ePLAR): A Differential Marker of Pre- and Postcapillary Pulmonary HypertensionDmitrij Oleynikov, Ma YiPulmonary Hypertension (PH) in dogs is a complicated syndrome that could be primary, due to idiopathic or genetic causes, or secondary due to pulmonary disease, pulmonary thromboembolism, heartworm disease, heart failure. Due to the inability of the routine use of right heart catheterization in veterinary patients, there is a lack of differential criteria between PH forms. This study was performed … …American Journal of Animal and Veterinary Sciences, Vol. 17, Issue 1 · 17 Feb 2022 · 6,793 accessesView PDFCite
Research ArticleOpen accessIn the abstractModern Metaheuristic with Multi-Objective Formulation for the Variable Selection ProblemLauro Cassio Martins de Paula, Anderson da Silva Soares, Telma Woerle Soares et al.The development of efficient algorithms for variable selection becomes important to deal with large and complex datasets. Most works in quantitative chemical analysis have used Genetic Algorithms (GAs) as a reference method to select variables. On the other hand, new advances in metaheuristic techniques provide novel possibilities in this task Moreover, the application of Multi-Objective Optimization (MOO) may significantly contribute … …Journal of Computer Science, Vol. 13, Issue 11 · 20 Nov 2017 · 7,668 accessesView PDFCite
EditorialOpen accessIn the abstractBig Data and Parkinson’s Disease - from Understanding of Disease to Personalised MedicineYen F. Tai, Nicola PaveseThe advancement of information technology in recent years has generated a huge amount of datasets in all areas of scientific research. This has led to new opportunities to harness the 'Big Data' to improve our understanding of diseases - from investigating disease mechanisms to monitoring treatment responses. The Big Data approach is a data-driven and often hypothesis-free, way of studying … …Neuroscience International, Vol. 7, Issue 1 · 27 Jul 2016 · 7,761 accessesView PDFCite
Research ArticleOpen accessIn the abstractMaximally Distant Codes Allocation Using Chemical Reaction Optimization and Ant Colony Optimization AlgorithmsTaisir Eldos, Waleed Nazih, Aws KananError correcting codes, also known as error controlling codes, are set of codes with redundancy that allows detecting errors. This is quite useful in transmitting data over a noisy channel or when retrieving data from a storage with possible physical defects. The idea is to use a set of code words that are maximally distant from each other, hence reducing … …Journal of Computer Science, Vol. 11, Issue 8 · 5 Nov 2015 · 7,004 accessesView PDFCite
Research ArticleOpen accessIn the abstractGenetic Algorithm for Variable and Samples Selection in Multivariate Calibration ProblemsKelton de Souza Santiago, Anderson Silva Soares, Telma Woerle de Lima et al.One of the main problems of quantitative analytical chemistry is to estimate the concentration of one or more species from the values of certain physicochemical properties of the system of interest. For this it is necessary to construct a calibration model, i.e., to determine the relationship between measured properties and concentrations. The multivariate calibration is one of the most successful … …Journal of Computer Science, Vol. 11, Issue 4 · 8 Jun 2015 · 7,385 accessesView PDFCite
Research ArticleOpen accessIn the abstractCLUSTERING TWEETS USING CELLULAR GENETIC ALGORITHMAmr Adel, Essam ElFakharany, Amr BadrAs the popularity of Twitter continues to increase rapidly, it is extremely necessary to analyze the huge amount of data that Twitter users generate. A popular method of tweet analysis is clustering. Because most tweets are textual, this study focuses on clustering tweets based on their textual content similarity. This study presents tweet clustering using cellular genetic algorithm cGA. The … …Journal of Computer Science, Vol. 10, Issue 7 · 16 Jun 2014 · 7,917 accessesView PDFCite
Research ArticleOpen accessIn the abstractA COMPARATIVE STUDY FOR RHODOPSIN PROTEIN FOLDING PROBLEMIman Ahmed Mahmoud, Amr Ahmed Badr, Mostafa Abdel AzimProteins are very important components in any living cells. A number of diseases such as Retinitis pigmentosa, Stargadt-like macular degeneration and Doyne Honeycomb Retinal Dystrophy (DHRD) diseases are shown to result from misfunctioning of proteins. Protein folding problem is a way to predict the best and optimal 3D molecular structure (tertiary structure) of a protein which is then considered to … …Journal of Computer Science, Vol. 10, Issue 10 · 6 May 2014 · 7,078 accessesView PDFCite
Research ArticleOpen accessIn the abstractVHDL DESIGN AND HARDWARE REALIZATION OF HYBRIDARTIFICIAL INTELLIGENCE ARCHITECTURERajeswaran Nagalingam, Tenneti Madhu, Munagala SuryakalavathiEvolutionary Algorithms (EA) use Genetic Algorithm (GA) in many optimization problems to efficiently compute the function value in less time. In this study the weight optimization of the Artificial Neural Net-work (ANN), using the Back Propagation Network (BPN), is tested and presented with GA. The combined architecture of Neuro-Genetic (Hybrid Artificial Intelligence) approach is proposed and simulated results are provided … …American Journal of Applied Sciences, Vol. 11, Issue 5 · 24 Feb 2014 · 6,570 accessesView PDFCite