CAD软件可重用机制的研究

基于软件重用技术与实例基技术间的相似性，在冲模ＣＡＤ软件可重用系统的研究中，用实例基推理技术实现了软件可重用思想。     

基于案例推理的房地产投资风险评价的研究

房地产项目是高利润、高风险的投资。为更加科学地评价其风险程度以便有效预控，提出将人工智能领域的新方法——案例推理应用到房地产投资风险评价的问题中。通过分析影响房地产投资风险的因素，结合案例推理的基本原理，提出了基于案例推理的房地产投资风险评价指标体系，并初步解决案例的表示、检索匹配以及案例学习等主要技术。     

改进的逆向推理技术在深基坑工程专家系统中的应用

将传统的逆向推理技术根据求解问题的特征进行改进，实现新的模糊推理算法及其网络结构。通过实际工程中的应用，说明该方法是合理的。     

Detecting modes of transport from unlabelled positioning sensor data

Global positioning systems (GPS) logs recorded in personal devices contain rich information such as travel patterns, locations of frequent visits and place–event associations. There have been rather successful attempts in detecting the mode of transport from GPS logs such as walking, driving or taking a bus, which has found varied applications. However, the best-known schemes either require tedious manual labelling or pre-training process (or both). We present MoDetect (MD), a unsupervised scheme which eliminates the need of manual labelling and pre-training while attaining equal or greater accuracy compared with the best-known supervised methods. MD can also cater for differences in individual's behaviours, and hence may be more widely applicable than the existing schemes. To achieve this, MD relies on Kolmogorov–Smirnov test which offers a theoretical assurance when computing similarity between segments of records. Our analysis shows that the higher speed modes can be better differentiated through a weighted bootstrapping procedure. We also augment the decisions with reference to the transfer probabilities between different modes at locations identified from the GPS records.     

A user-driven case-based reasoning tool for infilling missing values in daily mean river flow records

Missing data in river flow records represent a loss of information and a serious drawback in water management. In this work, we introduce gapIt, a user-driven case-based reasoning tool for infilling gaps in daily mean river flow records. Given a set of flow time series, gapIt builds a database of artificial gaps for which it computes several flow estimates, to find the best combinations of infilling algorithm and automatically selected donor station(s), according to state-of-the-art performance indicators. We obtained satisfactory results with Nash-Sutcliffe >0.7 for more than half of the ∼5000 synthetic gaps of various lengths and positions, randomly created along the available records. gapIt was evaluated on 24 daily river discharge time series recorded in Luxembourg over seven years from 01/01/2007 to 31/12/2013. We also discuss the benefits of coupling this approach with user-expertise for an improved infilling of real data gaps.     

Integrating a semantic-based retrieval agent into case-based reasoning systems: A case study of an online bookstore

Natural language search engines should be developed to provide a friendly environment for business-to-consumer e-commerce that reduce the fatigue customers experience and help them decide what to buy. To support product information retrieval and reuse, this paper presents a novel framework for a case-based reasoning system that includes a collaborative filtering mechanism and a semantic-based case retrieval agent. Furthermore, the case retrieval agent integrates short-text semantic similarity (STSS) and recognizing textual entailment (RTE). The proposed approach was evaluated using competitive methods in the performance of STSS and RTE, and according to the results, the proposed approach outperforms most previously described approaches. Finally, the effectiveness of the proposed approach was investigated using a case study of an online bookstore, and according to the results of case study, the proposed approach outperforms a compared system using string similarity and an existing e-commerce system, Amazon.     

Formalising the Fisherman's Folly puzzle

This paper investigates the challenging problem of encoding the common sense knowledge involved in the manipulation of spatial objects from a reasoning about actions and change perspective. In particular, we propose a formal solution to a puzzle composed of non-trivial objects (such as holes and strings) assuming a version of the Situation Calculus written over first-order Equilibrium Logic, whose models generalise the stable model semantics.     

属性强度函数未知下的煤炭资源采矿权案例估价方法

科学合理的煤炭资源采矿权估价方法有助于实现煤炭资源最优配置。随着煤炭资源采矿权交易市场的快速发展大,案例估价方法将在今后煤炭资源采矿权估价中变得越来越重要。本文基于案例推理和现代统计学等理论和方法,首先揭示了基于案例推理的煤炭资源采矿权估价基本原理,对属性指标、属性强度函数、标的资产、案例资产以及案例相似度等关键概念进行界定;然后建立了属性强度函数未知情形下的煤炭资源采矿权案例选取准则和相似度模型;最后建立了煤炭资源采矿权案例估价模型和估价流程。通过一煤炭资源采矿权实例,对该模型进行了运用研究。研究结果表明:一是运用煤炭资源采矿权案例估价方法估价出的结果非常接近该采矿权的最后交易价格;二是在存在一定数量的可比较交易对象前提下,案例估价方法较其他方法所需数据较少,也更为高效和直接。