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Forecasting urban water demand using different hybrid-based metaheuristic algorithms' inspire for extracting artificial neural network hyperparameters. [PDF]

Sci Rep
Zubaidi SL, Al-Bugharbee H, Alattabi AW, Ridha HM, Hashim K, Al-Ansari N, Yaseen ZM.   +6 more
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Optimizing Gaussian process regression (GPR) hyperparameters with three metaheuristic algorithms for viscosity prediction of suspensions containing microencapsulated PCMs. [PDF]

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Hai T, Basem A, Alizadeh A, Sharma K, Jasim DJ, Rajab H, Ahmed M, Kassim M, Singh NSS, Maleki H.   +9 more
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Towards secure IoT networks: A comprehensive study of metaheuristic algorithms in conjunction with CNN using a self-generated dataset. [PDF]

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Choudhary V, Tanwar S, Choudhury T, Kotecha K.   +3 more
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Optimization of carbon emission in an integrated machine-piece scheduling and vehicle routing problem and its solution using MOPSO and NSGAII metaheuristic algorithms. [PDF]

Sci Rep
Heidari A, Sheikh-Azadi AH, Hasan-Zadeh A, Kazemzadeh Y.   +3 more
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Predicting ground vibration during rock blasting using relevance vector machine improved with dual kernels and metaheuristic algorithms. [PDF]

Sci Rep
Fissha Y, Khatti J, Ikeda H, Grover KS, Owada N, Toriya H, Adachi T, Kawamura Y.   +7 more
europepmc   +1 more source

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A cooperative system for metaheuristic algorithms

Expert Systems with Applications, 2021
Abstract Optimization problems are defined as the functions whereby the target is to find the optimum state depending on the parameters that have certain limitations. In the field of optimization, the aim is to find from among multiple alternative solutions the optimal solution or approximate solution that provides all the restrictions. Metaheuristic
Baris Tekin Tezel, Ali Mert
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Brick-Up Metaheuristic Algorithms

2016 5th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI), 2016
Metaheuristic algorithms have been a very important topic in computer science since the start of evolutionary computing the Genetic Algorithms 1950s. By now these metaheuristic algorithms have become a very large family with successful applications in industry. A challenge which is always pondered on, is finding the suitable metaheuristic algorithm for
Qun Song 0004, Simon Fong 0001
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Metaheuristic anopheles search algorithm

Evolutionary Intelligence, 2020
Today, various optimization problems have been solved using different optimization techniques such as linear programming, nonlinear programming and dynamic programming. These methods mainly try to find optimal solution in the proximity of starting point.
Hossein Baloochian, Hamid Reza Ghaffary, Saeed Balochian   +2 more
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Hybrid Metaheuristic Algorithm for Clustering

2018 IEEE Symposium Series on Computational Intelligence (SSCI), 2018
Clustering involves grouping a collection of data objects into meaningful or useful categories such that objects within the same category are similar to one another while objects in different categories are dissimilar. Clustering is a challenging problem with diverse practical applications that span multiple research domains.
Olayinka Idowu Oduntan, Parimala Thulasiraman   +1 more
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Automated Design of Metaheuristic Algorithms

2018
The design and development of metaheuristic algorithms can be time-consuming and difficult for a number of reasons including the complexity of the problems being tackled, the large number of degrees of freedom when designing an algorithm and setting its numerical parameters, and the difficulties of algorithm analysis due to heuristic biases and ...
Stützle, Thomas, López-Ibáñez, Manuel   +1 more
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