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Author Archives: Yarpiz

Group Method of Data Handling (GMDH) in MATLAB

Group Method of Data Handling (GMDH) is a family of mathematical modeling and nonlinear regression algorithms, which is originally proposed by Alexey Grigorevich Ivakhnenko, an Ukrainian scientist and mathematician, in 1968. This approach is also known as Polynomial Neural Network and can be assumed as a specific type of supervised Artificial Neural Network (ANN). In addition to modeling specifications, GMDH ...

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Firefly Algorithm (FA) in MATLAB

Firefly Algorithm (FA) is a metaheuristic algorithm for global optimization, which is inspired by flashing behavior of firefly insects. This algorithm is proposed by Xin-She Yang in 2008. Fireflies use the flashing behavior to attract other fireflies, usually for sending signals to opposite sex. However, in the mathematical model, used inside Firefly Algorithm, simply the fireflies are unisex, and any ...

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DBSCAN Clustering in MATLAB

Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is a density-based clustering algorithm, proposed by Martin Ester et al., 1996. The algorithm finds neighbors of data points, within a circle of radius ε, and adds them into same cluster. For any neighbor point, which its ε-neighborhood contains a predefined number of points, the cluster is expanded to contain its neighbors, ...

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Invasive Weed Optimization (IWO) in MATLAB

Invasive Weed Optimization (IWO) is a nature-inspired metaheuristic, inspired by spreading strategy of weeds, and proposed by Alireza Mehrabian and Caro Lucas, in 2006. Based on the r/K Selection Theory, the artificial weeds (solutions) use the r-Selection strategy in the beginning of algorithms, and gradually they switch to K-Selection strategy, as algorithm continues to running. For more information on the ...

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Imperialist Competitive Algorithm (ICA) in MATLAB

Imperialist Competitive Algorithm (ICA), also known as Colonial Competitive Algorithm (CCA), is a sociopolitical metaheuristics, inspired by historical colonization process and competition among imperialists, to capture more colonies. Set of countries (solutions) in ICA, is partitioned to form several Empires, which contains a single Imperialist and several other weaker countries, called Colonies. This algorithm is proposed by Esmaeil Atashpaz Gargari ...

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Tabu Search (TS) in MATLAB

Tabu Search (TS) is a local search-based metaheuristic, which is proposed by Fred W. Glover, in 1986. Tabu Search is completely based on the definition of neighborhood and actions converting a solution to its neighboring solutions. This algorithms starts with a single solution, and searches for better solutions, applying actions and moving between neighbor solutions. However, acceptance, applicability and availability ...

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Biogeography-Based Optimization (BBO) in MATLAB

Biogeography-Based Optimization (BBO) is an evolutionary algorithm and metaheuristic, which is inspired by the biogeographic concepts: speciation (the evolution of new species), the migration of species between islands, and the extinction of species. The algorithm is originally proposed by Dan Simon, in 2008, in this paper. This algorithm is based on a mathematical model, describing the migration of species between ...

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CMA-ES in MATLAB

Evolution Strategy (ES) is the first and oldest evolutionary algorithm, and it is based on the adaptation and evolution. Specially, the main concept used to describe how Evolution Strategy works, is the Evolution of Evolution. In fact, evolution strategy is a family of related algorithms, and because of this, the plural name Evolution Strategies is also widely used, in the ...

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Differential Evolution (DE) in MATLAB

Differential Evolution (DE) is an evolutionary algorithm, which uses the difference of solution vectors to create new candidate solutions. The key points, in the usage of population differences in proposition of new solutions, are: The distribution of population and its orientation is hidden in the differences of population members. According to the Central Limit Theorem, as the population size increases, ...

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Simulated Annealing in MATLAB

Simulated Annealing (SA) is a metaheuristic, inspired by annealing process. SA starts with an initial solution at higher temperature, where the changes are accepted with higher probability. So the exploration capability of the algorithm is high and the search space can be explored widely. As the algorithm continues to run, the temperature decreases gradually, like the annealing process, and the ...

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