Pattern recognition and image analysis
Pattern recognition and image analysis
From data mining to knowledge discovery: an overview
Advances in knowledge discovery and data mining
A statistical perspective on knowledge discovery in databases
Advances in knowledge discovery and data mining
Self-Organizing Methods in Modeling: Gmdh Type Algorithms
Self-Organizing Methods in Modeling: Gmdh Type Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Data Warehouse: From Architecture to Implementation
Data Warehouse: From Architecture to Implementation
Data Mining and Knowledge Discovery for Process Monitoring and Control
Data Mining and Knowledge Discovery for Process Monitoring and Control
Neural Networks for Identification, Prediction, and Control
Neural Networks for Identification, Prediction, and Control
Bayesian networks based rare event prediction with sensor data
Knowledge-Based Systems
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Data mining is the exploration and analysis, by automatic or semiautomatic means, of large quantities of data in order to discover meaningful patterns and rules. Data mining consists of several tasks and each task uses a variety of methodologies. Some of these tasks are suited for a top-down method called hypothesis testing and others are suited for a bottom-up method called knowledge discovery. In this paper, we report our research procedures and results that concern and relate ozone concentration data in various factors and attributes. We use the general steps of directed knowledge discovery methodologies and intelligent modeling techniques. Next, we construct ozone concentration prediction system in order to reduce various adverse effects on human beings and life on the earth.