scholarly journals THE USE OF PETRI NETS IN DECISION SUPPORT SYSTEMS BASED ON INTELLIGENT MULTIPLY SOURCE DATA ANALYSIS

2017 ◽  
Vol 7 (4) ◽  
pp. 24-27
Author(s):  
Tomasz Rymarczyk ◽  
Grzegorz Kłosowski ◽  
Tomasz Cieplak
Keyword(s):  
Decision Support ◽  
Data Analysis ◽  
Decision Support System ◽  
Petri Nets ◽  
Support System ◽  
Petri Net ◽  
General Scheme ◽  
Optimal Solution ◽  
Source Data ◽  
Service Oriented

The paper deals with the design of data analysis systems for business process automation. A general scheme of decision support system was developed in which one of the modules is based on Petri Nets. The way of implementation of Petri Net model in optimization problem regarding service-oriented decision support system was shown. The Petri Net model of distribution workflow was presented and simulation experiments was completed. As a result the optimal solution as a set of parameters was emerged.

Network-aware credit scoring system for telecom subscribers using machine learning and network analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hongming Gao ◽  
Hongwei Liu ◽  
Haiying Ma ◽  
Cunjun Ye ◽  
Mingjun Zhan
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Scoring System ◽  
Credit Scoring ◽  
Prediction Performance ◽  
Content Type ◽  
Connected Subgroup ◽  
Source Data ◽  
Credit Scores

PurposeA good decision support system for credit scoring enables telecom operators to measure the subscribers' creditworthiness in a fine-grained manner. This paper aims to propose a robust credit scoring system by leveraging latent information embedded in the telecom subscriber relation network based on multi-source data sources, including telecom inner data, online app usage, and offline consumption footprint.Design/methodology/approachRooting from network science, the relation network model and singular value decomposition are integrated to infer different subscriber subgroups. Employing the results of network inference, the paper proposed a network-aware credit scoring system to predict the continuous credit scores by implementing several state-of-art techniques, i.e. multivariate linear regression, random forest regression, support vector regression, multilayer perceptron, and a deep learning algorithm. The authors use a data set consisting of 926 users of a Chinese major telecom operator within one month of 2018 to verify the proposed approach.FindingsThe distribution of telecom subscriber relation network follows a power-law function instead of the Gaussian function previously thought. This network-aware inference divides the subscriber population into a connected subgroup and a discrete subgroup. Besides, the findings demonstrate that the network-aware decision support system achieves better and more accurate prediction performance. In particular, the results show that our approach considering stochastic equivalence reveals that the forecasting error of the connected-subgroup model is significantly reduced by 7.89–25.64% as compared to the benchmark. Deep learning performs the best which might indicate that a non-linear relationship exists between telecom subscribers' credit scores and their multi-channel behaviours.Originality/valueThis paper contributes to the existing literature on business intelligence analytics and continuous credit scoring by incorporating latent information of the relation network and external information from multi-source data (e.g. online app usage and offline consumption footprint). Also, the authors have proposed a power-law distribution-based network-aware decision support system to reinforce the prediction performance of individual telecom subscribers' credit scoring for the telecom marketing domain.

Application of Multidimensional Data Analysis in Power Marketing Decision Support System Based on Big Data

2016 ◽  
Vol 9 (10) ◽  
pp. 295-304
Author(s):  
Sun Zhineng ◽  
Yu Fang ◽  
Zhou Kaihe ◽  
Li Jiangang ◽  
Fang Yunhui
Keyword(s):  
Big Data ◽  
Decision Support ◽  
Data Analysis ◽  
Decision Support System ◽  
Support System ◽  
Multidimensional Data ◽  
Multidimensional Data Analysis ◽  
Marketing Decision

scholarly journals Decision support system for Petri nets enabled automation components

2009 ◽  
Author(s):  
Jodo Pinto ◽  
J. Marco Mendes ◽  
Paulo Leitao ◽  
Armando W. Colombo ◽  
Axel Bepperling ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Petri Nets ◽  
Support System

scholarly journals Big Data Analysis with MongoDB for Decision Support System

2016 ◽  
Vol 14 (3) ◽  
pp. 1083 ◽  
Author(s):  
Sulistyo Heripracoyo ◽  
Roni Kurniawan
Keyword(s):  
Big Data ◽  
Decision Support ◽  
Data Analysis ◽  
Decision Support System ◽  
Support System ◽  
Big Data Analysis

A data analysis decision support system for the carbon dioxide capture process

2009 ◽  
Vol 36 (6) ◽  
pp. 9949-9960 ◽  
Author(s):  
Yuxiang Wu ◽  
Christine W. Chan
Keyword(s):  
Carbon Dioxide ◽  
Decision Support ◽  
Data Analysis ◽  
Decision Support System ◽  
Support System ◽  
Carbon Dioxide Capture ◽  
Capture Process
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