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991.
Intelligent policy recommendations on enterprise resource planning by the use of agent technology and data mining techniques 总被引:3,自引:0,他引:3
Andreas L. Symeonidis Dionisis D. Kehagias Pericles A. Mitkas 《Expert systems with applications》2003,25(4):736-602
Enterprise Resource Planning systems tend to deploy Supply Chain Management and/or Customer Relationship Management techniques, in order to successfully fuse information to customers, suppliers, manufacturers and warehouses, and therefore minimize system-wide costs while satisfying service level requirements. Although efficient, these systems are neither versatile nor adaptive, since newly discovered customer trends cannot be easily integrated with existing knowledge. Advancing on the way the above mentioned techniques apply on ERP systems, we have developed a multi-agent system that introduces adaptive intelligence as a powerful add-on for ERP software customization. The system can be thought of as a recommendation engine, which takes advantage of knowledge gained through the use of data mining techniques, and incorporates it into the resulting company selling policy. The intelligent agents of the system can be periodically retrained as new information is added to the ERP. In this paper, we present the architecture and development details of the system, and demonstrate its application on a real test case. 相似文献
992.
Intelligent remote monitoring and diagnosis of manufacturing processes using an integrated approach of neural networks and rough sets 总被引:5,自引:0,他引:5
This research develops a methodology for the intelligent remote monitoring and diagnosis of manufacturing processes. A back propagation neural network monitors a manufacturing process and identifies faulty quality categories of the products being produced. For diagnosis of the process, rough set is used to extract the causal relationship between manufacturing parameters and product quality measures. Therefore, an integration of neural networks and a rough set approach not only provides information about what is expected to happen, but also reveals why this has occurred and how to recover from the abnormal condition with specific guidelines on process parameter settings. The methodology is successfully implemented in an Ethernet network environment with sensors and PLC connected to the manufacturing processes and control computers. In an application to a manufacturing system that makes conveyor belts, the back propagation neural network accurately classified quality faults, such as wrinkles and uneven thickness. The rough set also determined the causal relationships between manufacturing parameters, e.g., process temperature, and output quality measures. In addition, rough set provided operating guidelines on specific settings of process parameters to the operators to correct the detected quality problems. The successful implementation of the developed methodology also lays a solid foundation for the development of Internet-based e-manufacturing. 相似文献
993.
The randomly and unpredictable user behaviors during a multimedia presentation may cause the long retrieval latency in the client–server connection. To accommodate the above problem, we propose a prefetching scheme that using the association rules from the data mining technique. The data mining technique can provide some priority information such as the support, confidence, and association rules which can be utilized for prefetching continuous media. Thus, using the data mining technique, the proposed prefetching policy can predict user behaviors and evaluate segments that may be accessed in near future. The proposed prefetching scheme was implemented and tested on synthetic data to estimate its effectiveness. Performance experiments show that the proposed prefetching scheme is effective in improving the latency reduction, even for small cache sizes. 相似文献
994.
Complete Mining of Frequent Patterns from Graphs: Mining Graph Data 总被引:16,自引:0,他引:16
Basket Analysis, which is a standard method for data mining, derives frequent itemsets from database. However, its mining ability is limited to transaction data consisting of items. In reality, there are many applications where data are described in a more structural way, e.g. chemical compounds and Web browsing history. There are a few approaches that can discover characteristic patterns from graph-structured data in the field of machine learning. However, almost all of them are not suitable for such applications that require a complete search for all frequent subgraph patterns in the data. In this paper, we propose a novel principle and its algorithm that derive the characteristic patterns which frequently appear in graph-structured data. Our algorithm can derive all frequent induced subgraphs from both directed and undirected graph structured data having loops (including self-loops) with labeled or unlabeled nodes and links. Its performance is evaluated through the applications to Web browsing pattern analysis and chemical carcinogenesis analysis. 相似文献
995.
On Using a Warehouse to Analyze Web Logs 总被引:1,自引:0,他引:1
Analyzing Web Logs for usage and access trends can not only provide important information to web site developers and administrators, but also help in creating adaptive web sites. While there are many existing tools that generate fixed reports from web logs, they typically do not allow ad-hoc analysis queries. Moreover, such tools cannot discover hidden patterns of access embedded in the access logs. We describe a relational OLAP (ROLAP) approach for creating a web-log warehouse. This is populated both from web logs, as well as the results of mining web logs. We discuss the design criteria that influenced our choice of dimensions, facts and data granularity. A web based ad-hoc tool for analytic queries on the warehouse was developed. We present some of the performance specific experiments that we performed on our warehouse. 相似文献
996.
For more than a decade, researchers have actively explored the area of image/video analysis and retrieval. Yet one fundamental
problem remains largely unsolved: how to measure perceptual similarity between two objects. For this purpose, most researchers
employ a Minkowski-type metric. Unfortunately, the Minkowski metric does not reliably find similarities in objects that are
obviously alike. Through mining a large set of visual data, our team has discovered a perceptual distance function. We call
the discovered function the dynamic partial function (DPF). When we empirically compare DPF to Minkowski-type distance functions in image retrieval and in video shot-transition
detection using our image features, DPF performs significantly better. The effectiveness of DPF can be explained by similarity theories in cognitive psychology. 相似文献
997.
998.
分析了模糊逻辑规则的形成过程,介绍了模糊推理方法,提出了基于模糊规则化的数据挖掘方法。由分析可以看出,基于模糊逻辑规则的方法能从大量的数据集合中有效地发现有价值但不明显的信息并挖掘出有价值的信息。例如,在银行借贷中,根据数据库中的数据对借贷方进行评估,挖掘出影响贷款安全的有关单位信息等。 相似文献
999.
1000.