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Titlebook: Enterprise Information Systems V; Olivier Camp,Joaquim B. L. Filipe,Mario Piattini Conference proceedings 2005 Springer Science+Business M

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樓主: Racket
51#
發(fā)表于 2025-3-30 11:23:01 | 只看該作者
ERP Systems Implementation Determinants and Success Measures in China: A Case Study Approachosts, improve customer service to obtain competitive advantage against their competitors. Manufacturing companies are forced to adopt new methods to achieve the above objectives. Enterprise resource planning (ERP) system is one of the most widely accepted choices. Significant benefits such as improv
52#
發(fā)表于 2025-3-30 13:17:02 | 只看該作者
53#
發(fā)表于 2025-3-30 18:05:49 | 只看該作者
Building Intelligent Credit Scoring Systems Using Decision Tablessecond criterion and propose the use of decision tables as an alternative knowledge visualisation formalism which lends itself very well to building intelligent and user-friendly credit scoring systems. Starting from a set of propositional if-then rules extracted by a neural network rule extraction
54#
發(fā)表于 2025-3-31 00:20:58 | 只看該作者
55#
發(fā)表于 2025-3-31 03:50:24 | 只看該作者
Partial Abductive Inference in Bayesian Networks by Using Probability Treesdence propagation or total abduction. When join trees are used as the graphical structure over which propagation will be carried out, the problem can be decomposed into two stages: (1) to obtain a join tree containing only the variables included in the explanation set, and (2) to solve a total abduc
56#
發(fā)表于 2025-3-31 05:03:36 | 只看該作者
57#
發(fā)表于 2025-3-31 11:09:06 | 只看該作者
58#
發(fā)表于 2025-3-31 17:18:57 | 只看該作者
Building Intelligent Credit Scoring Systems Using Decision Tablesntelligent and user-friendly credit scoring systems. Starting from a set of propositional if-then rules extracted by a neural network rule extraction algorithm, we construct decision tables and demonstrate their efficiency and user-friendliness for two real-life credit scoring cases.
59#
發(fā)表于 2025-3-31 20:45:08 | 只看該作者
The ‘New Inflation’ and Monetary Policyce. It is possible to say what will happen, but it is very diificult to asy when. Reasons for this conclusion are presented beginning with the drivers of change for Information Technology, and the drivers of change for human industry.
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