An important problem in economics and other areas of science is finding the mathematical relationship between the empirically observed variables measuring a system. In many conventional modeling techniques, one necessarily begins by selecting the size and shape of the mathematical model. Because the the vast majority of available mathematical tools only handle linear models, this choice is often simply a linear model. After making this choice, one usually then tries to find the values of certain coefficients and constants required by the particular model so as to achieve the best fit between the observed data and the model. But, in many cases, the most important issue is the size and shape of the mathematical model itself. That is, one real...
A Computer program based on the genetic approach has been developed by the author as a supplementary...
Abstract- In this paper, we describe some evolutionary approaches based on genetic algorithms to fac...
The genetic algorithm can be applied to selecting theoretical probability distributions so as to be ...
Typically, economists develop models by first selecting a model structure based on theoretical consi...
This paper describes an evolutionary method for identifying a causal model from the ob-served time s...
: This paper reports on a new "genetic computing" paradigm for solving problems. In this ...
Automatic model search procedures aim at identifying the model that maximises a given fitness functi...
none2-tness function, thereby treating model selection as an optimisation problem. However, it is u...
Abstract. A real-world system has often plenty of variables that affect its behaviour. To be able to...
-tness function, thereby treating model selection as an optimisation problem. However, it is unreali...
This study provides a short introduction and an overview of the basics of genetic programming (GP) a...
AbstractIn time series analysis, we often find the trend of dynamic data changing with time. Using ...
Synopsis By making use of genetic programming, empirical models for metallurgical processes can be e...
This paper discusses a tool for optimization of econometric models based on genetic algorithms. Firs...
1. Efforts to understand the links between evolutionary and ecological dynamics hinge on our ability...
A Computer program based on the genetic approach has been developed by the author as a supplementary...
Abstract- In this paper, we describe some evolutionary approaches based on genetic algorithms to fac...
The genetic algorithm can be applied to selecting theoretical probability distributions so as to be ...
Typically, economists develop models by first selecting a model structure based on theoretical consi...
This paper describes an evolutionary method for identifying a causal model from the ob-served time s...
: This paper reports on a new "genetic computing" paradigm for solving problems. In this ...
Automatic model search procedures aim at identifying the model that maximises a given fitness functi...
none2-tness function, thereby treating model selection as an optimisation problem. However, it is u...
Abstract. A real-world system has often plenty of variables that affect its behaviour. To be able to...
-tness function, thereby treating model selection as an optimisation problem. However, it is unreali...
This study provides a short introduction and an overview of the basics of genetic programming (GP) a...
AbstractIn time series analysis, we often find the trend of dynamic data changing with time. Using ...
Synopsis By making use of genetic programming, empirical models for metallurgical processes can be e...
This paper discusses a tool for optimization of econometric models based on genetic algorithms. Firs...
1. Efforts to understand the links between evolutionary and ecological dynamics hinge on our ability...
A Computer program based on the genetic approach has been developed by the author as a supplementary...
Abstract- In this paper, we describe some evolutionary approaches based on genetic algorithms to fac...
The genetic algorithm can be applied to selecting theoretical probability distributions so as to be ...