The state-of-the-art data mining technologies, genetic programming, has been applied to develop depth varying thermal structure. The model results are verified by using field-monitoring data in the South China Sea.doi:10.1142/9789812702838_0210Vladan BabovicHong Zhang
Predictive mobility support for QoS provisioning in mobile wireless environments IEEE J. Select. Area Commun. (2001) A. Nanopoulos, D. Katsaros, Y. Manolopoulos, Effective prediction of web user accesses: a data mining approach, in:... A. Nanopoulos et al. A data mining algorithm for gene...
Fig. 1. TOB optimized data matching methodology configured for predicting and data mining highly skewed carbon-flux (net ecosystem carbon exchange; NEE) datasets. TOB Stage 1 assesses data-record matches between records in small, evenly distributed subset designed to tune the algorithm with a larger...
Big data analysis is a data mining technique that can be used in many sectors – economic, industrial and commercial. Data mining can be defined as preparing, visualizing and exploring massive databases (Parr & Vaudrevange, 2020), whereas the techniques for discovering patterns from these ...
To keep current clients, a corporation needs to analyze data in the customer database to determine the reasons for their departure2. The basic goal of customer churn prediction is to identify customers who are likely to leave the company. Avoiding client churn has become a critical goal for ...
Classification in Large Databases Classification—a classical problem extensively studied by statisticians and machine learning researchers Scalability: Classifying data sets with millions of examples and hundreds of attributes with reasonable speed Why decision tree induction in data mining? relatively faster ...
Classification is one of the supervised learning methods in data mining. The main goal of classification is to connect the input variables with the target variables and make predictions based on this relationship. The classification techniques used in this study ranged from decision tree to support ...
It is a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting--...
There are a number of basic tasks that are frequently carried out as part of data mining, many of which may be tackled using a number of different approaches. In this study, we follow a procedure for data mining: the SAS SEMMA methodology [16]. Fig. 1 shows the SEMMA process. This ...
With regard to the application of data-mining techniques, the variation in length on the rake side (upper length) and in the length on the relief side has been considered (down length) for each lobe, as well as the variation in the total length of each lobe. Two types of wear are ...