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Titlebook: Applications of Data Management and Analysis; Case Studies in Soci Mohammad Moshirpour,Behrouz H. Far,Reda Alhajj Book 2018 Springer Nature

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Artificial Neural Network Modeling and Forecasting of Oil Reservoir Performance,ministic, cumbersome, and expensive (manpower and time-consuming). Presence of a high-dimensional data space consisting of a large number of operational and geological parameters impedes practical decision-making and future performance prediction for oil and gas recovery processes. Thus, the rise of
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A Fuzzy Dynamic Model for Customer Churn Prediction in Retail Banking Industry, generate stable profits, the main focus of the organizations is based on customer retention..This research aims to develop a three-phase framework for fuzzy dynamic churn prediction of high-value customers. Three steps include identification of high-value customers, determination of the degree of c
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A New 3D Value Model for Customer Segmentation: Complex Network Approach,ustomer’s value during his or her lifetime (CLV) is an effective solution to identify and segment customers. Network potential, one of the most important components of CLV, can cause more income and affect the customers’ referrals and network relationships. This research has a new attitude to custom
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Finding Influential Factors for Different Types of Cancer: A Data Mining Approach,rstand the process of cancer development and find new ways of preventing the disease. Most of the researches done on cancer datasets focus only one type of cancer. This research aims to provide a new methodology for extracting significant influential factors affecting multiple cancer types by employ
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Enhanced Load Balancer with Multilayer Processing Architecture for Heavy Load Over Cloud Network,me period. The different types of algorithms for load balancing over cloud environment have been implemented with the main goal to develop cloud resources easily accessible to the end users. The main load balancing problem is the runtime overload owed to the change of load data among CPUs, selection
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