Results 11 to 20 of about 102,518 (248)
The Effect of Multi-Generational Selection in Geometric Semantic Genetic Programming
Applied Sciences, 2022 Among the evolutionary methods, one that is quite prominent is genetic programming. In recent years, a variant called geometric semantic genetic programming (GSGP) was successfully applied to many real-world problems.
Mauro Castelli +4 more
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Forecasting and forecast-combining of quarterly earnings-per-share via genetic programming
Estudios de Administración, 2008 In this study we examine different methodologies to estimate earnings. More specifically, we evaluate the viability of Genetic Programming as both a forecasting model estimator and a forecast-combining methodology.
Arturo Rodríguez, Joaquín Trigueros
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Algorithms, 2021 Genetic Algorithms are stochastic optimization methods where solution candidates, complying to a specific problem representation, are evaluated according to a predefined fitness function.
Jalal Al-Afandi, András Horváth
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PENDEKATAN ALGORITMA GENETIKA DALAM MENYELESAIKAN PERMASALAHAN FUZZY LINEAR PROGRAMMING
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2011 Fuzzy linear programming is one of the linear programming developments which able to accommodate uncertainty in the real world. Genetic algorithm approach in solving linear programming problems with fuzzy constraints has been introduced by Lin (2008) by ...
Siska Dewi Lestari, Subanar Subanar
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Bias-variance decomposition in Genetic Programming
Open Mathematics, 2016 We study properties of Linear Genetic Programming (LGP) through several regression and classification benchmarks. In each problem, we decompose the results into bias and variance components, and explore the effect of varying certain key parameters on the
Kowaliw Taras, Doursat René
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Forecasting Shaharchay River Flow in Lake Urmia Basin using Genetic Programming and M5 Model Tree
مجله آب و خاک, 2017 Introduction: Precise prediction of river flows is the key factor for proper planning and management of water resources. Thus, obtaining the reliable methods for predicting river flows has great importance in water resource engineering.
S. Samadianfard, R. Delirhasannia
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Genetic Programming-Based Machine Degradation Modeling Methodology
IEEE Open Journal of Instrumentation and Measurement, 2022 Machine degradation is a complex, dynamic and irreversible process and its modeling is a leading-edge technology in prognostics and health management (PHM).
Tongtong Yan, Dong Wang
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The Train Delay Model Developed by the Genetic Programming Algorithm
Journal of Advanced Transportation, 2022 The paper discusses the problem of probability distribution category identification of train delay data by a genetic programming algorithm. This train delay frequency function and the probability distribution simply derived from it are significant to ...
Tomas Brandejsky
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Evolutionary Algorithms in a Bacterial Consortium of Synthetic Bacteria
Algorithms, 2023 At present, synthetic biology applications are based on the programming of synthetic bacteria with custom-designed genetic circuits through the application of a top-down strategy. These genetic circuits are the programs that implement a certain algorithm,
Sara Lledó Villaescusa +1 more
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On Comprehension of Genetic Programming Solutions: A Controlled Experiment on Semantic Inference
Mathematics, 2022 Applied to the problem of automatic program generation, Genetic Programming often produces code bloat, or unexpected solutions that are, according to common belief, difficult to comprehend.
Boštjan Slivnik +3 more
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