Results 11 to 20 of about 92,765 (267)
From Requirements to Source Code: Evolution of Behavioral Programs
Applied Sciences, 2022 Automatically generating executable code has a long history of arguably modest success, mostly limited to the generation of small programs of up to 200 lines of code, and genetic improvement of existing code. We present the use of genetic programming (GP)
Roy Poliansky +2 more
doaj +1 more source
Route Stability in the Uncertain Capacitated Arc Routing Problem
Frontiers in Energy Research, 2022 Power line inspections in a microgrid can be modeled as the uncertain capacitated arc routing problem, which is a classic combinatorial optimization problem.
Yuxin Liu +3 more
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source