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Since 1960, the pavement serviceability index has supported the efforts of engineers who make decisions concerning maintenance strategies. The data of pavement surfaces do not belong to a normal distribution. Because the data violate the basic assumptions of linear regression, the pavement serviceability index is not suitable for regression modeling. Many kinds of prediction models with non-statistical...
Fuzzy Logic Controllers (FLCS) are rule-based system that successfully incorporate the flexibility of human-decision making by means of the use of fuzzy set theory. This paper provides an overview on evolutionary learning methods for the automated design and optimization of fuzzy logic controllers. A three-stage evolution framework that uses Genetic Programming (GP) and Genetic Algorithms (GAS) evolves...
In this paper, a fuzzy model based on genetic programming (GPFM) is proposed to diagnose the fault types of insulation of power transformers. The proposed GPFM algorithm constructs the fuzzy relationship between input and output fuzzy variables by genetic programming algorithms. The parameters of memberships of fuzzy subsets and the fuzzy relationship of system are represented by the GP candidates...
Fuzzy classifiers and fuzzy rules are powerful tools in data mining and knowledge discovery. In this work, intrusion detection is approached as a data mining task and genetic programming is deployed to evolve fuzzy classifiers for detection of intrusion and security problems. We train the fuzzy classifier on a data set modeled as a fuzzy information retrieval collection and investigate its ability...
In affective product design, one of the main goals is to maximize customers' affective satisfaction by optimizing design variables of a new product. To achieve this, a model in relating customers' affective responses and design variables of a new product is required to be developed based on customers' survey data. However, previous research on modelling the relationship between affective response...
In this paper various restrictions are proposed in the construction of hierarchical fuzzy rule bases by using Genetic and Bacterial Programming algorithms in order to model black box systems defined by input-output pairs, i.e. to solve supervised machine learning problems. The properties (learning speed, accuracy) of the established systems are observed based on simulation results and they are compared...
Biology, Psychology and Social Sciences are intrinsically connected to the very roots of the development of algorithms and methods in Computational Intelligence, as it is easily seen in approaches like genetic algorithms, evolutionary programming and particle swarm optimization. In this work we propose a new optimization method based on dialectics using fuzzy membership functions to model the influence...
This paper presents an unified framework for fast interactive segmentation of natural images using the image foresting transform (IFT) - a tool for the design of image processing operators based on connectivity functions (path-value functions) in graphs derived from the image. It mainly consists of three tasks: recognition, enhancement, and extraction. Recognition is the only interactive task, where...
This paper presents G-REX, a versatile data mining framework based on genetic programming. What differs G-REX from other GP frameworks is that it doesn't strive to be a general purpose framework. This allows G-REX to include more functionality specific to data mining like preprocessing, evaluation- and optimization methods, but also a multitude of predefined classification and regression models. Examples...
Fuzzy models have capability for solving problem in different application such as pattern recognition, prediction and control. Nevertheless, it has to be emphasized that the identification of a fuzzy model is complex task with many local minima. Cartesian genetic programming provides a way to solve such complex optimization problem. In this paper, fuzzy model is in form of network. Cartesian genetic...
An evolutionary system for derivation of fuzzy classification rules is presented. This system uses two populations: one of fuzzy classification rules, and one of membership function definitions. A constrained-syntax genetic programming evolves the first population and a mutation-based evolutionary algorithm evolves the second population. These two populations co-evolve to better classify the underlying...
In the early days a policy was a set of simple rules with a clear intuitive motivation that could be formalised to good effect. However the world is now much more complex. Subtle risk decisions may often need to be made and people are not always adept at expressing rationale for what they do. Previous research has demonstrated that Genetic Programming can be used to infer statements of policies from...
A genetic programming based fuzzy mapping functions (GPFMF) model is proposed in this paper to diagnose the insulation fault types of power transformers. The proposed GPFMF model constructs the fuzzy relationship between input and output fuzzy variables by genetic programming algorithms. The fuzzy relationship is represented as one of candidates which have the form of tree-like combinations of series...
When aggregating multiple items together, for processes such as decision making, it is often beneficial to assign linguistically imprecise weights to each criterion. These weights, when coupled with the values of the criteria, enable us to prioritize certain responses over others. Through the advent of fuzzy connectives, computers can also emulate this weight-biased, decision-making behavior. However,...
Accuracy in processing time estimation of manufacturing operations is fundamental to achieve more competitive prices and higher profits in an industry. The manufacturing times of a machine depend on several input variables and, for each class or type of product, a regression function for that machine can be defined. Time estimations are used for implementing production plans. These plans are usually...
In this contribution, we present GP-COACH, a novel GFS based on the cooperative-competitive learning approach, that uses genetic programming to code fuzzy rules with a different number of variables, for getting compact and accurate rule bases for high dimensional problems. GP-COACH learns disjunctive normal form rules (generated by means of a context-free grammar) and uses a token competition mechanism...
The technique for building of intellectual control system fuzzy knowledgebase for information communication networks and services is proposed in this paper. This technique consists of two phases: structure creation and membership function parameters adjustments. This technique allows accelerate the fuzzy knowledgebase creation.
In this paper we present a framework for 3D hand tracking and dynamic gesture recognition using a single camera. Hand tracking is performed in a two step process: we first generate 3D hand posture hypothesis using geometric and kinematics inverse transformations, and then validate the hypothesis by projecting the postures on the image plane and comparing the projected model with the ground truth using...
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