Titlebook: Knowledge Engineering and Management; Proceedings of the E Zhenkun Wen,Tianrui Li Conference proceedings 2014 Springer-Verlag Berlin Heidel

Factual

臆斷

chassis

性行為放縱者

parallelism

Parallel Approaches to Neighborhood Rough Sets: Classification and Feature Selection,ce, which is really a challenge for the existing data analysis methods. Traditional algorithms, such as classification and feature selection under neighborhood rough sets, have been proved to be very effective in real applications. Parallel approach to these traditional algorithms could be a way to

commensurate

Geometry Knowledge Base Learning from Theorem Proofs, almost structural mathematics language. Hence, it is possible to let computer understand geometry theorem proofs. Based on the process ontology, a novel geometry knowledge base (GKB) in this paper is built by letting computer learn from theorem proofs. The resulting process ontology is automaticall

PIZZA

Return Forecast of Subscription for New Shares in Growth Enterprise Market Using Simulation Method,nclusions. One is that investors can make more profit by selling their new shares at closing price than at opening price in the first trading day, the other is that percentage increase of a new stock in the first trading day has a bigger impact than the rate of successful subscription for new shares

cancer

An Incremental Learning Approach for Updating Approximations in Rough Set Model Over Dual-Universesve way to use incremental updating approximations method in the dynamic environment to better support data mining-related tasks based on RST. In this paper, we propose an incremental learning approach for updating approximations in RSMDU when the objects of two universes vary with time. An illustrat

戰(zhàn)役

Research on Risk Assessment of Ship Repair Based on Case-Based Reasoning,this paper identifies the causes and consequences of risk, and utilizes frame-based representation to construct the case representation for ship repair risk. In addition, similarity functions are developed for enumerated attributes, numeric attributes, and fuzzy attributes, so as to perform reasonin

編輯才信任

,A Rule-Based Inference Method Using Dempster–Shafer Theory,oning method based on rule-base with certainty interval is investigated. First, knowledge representation with interval uncertainty is defined and the matching principle is given. Then, a rule-based inference method under interval numbers using Dempster–Shafer theory is derived. A numerical example i