14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings.最新文献_第5页

14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings. Pub Date : 2002-11-04 DOI: 10.1109/TAI.2002.1180825

N. Bourbakis

引用次数: 3

Function approximation using robust wavelet neural networks 鲁棒小波神经网络的函数逼近

14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings. Pub Date : 2002-11-04 DOI: 10.1109/TAI.2002.1180842

Sheng-Tun Li, Shu‐Ching Chen

引用次数: 46

Local search algorithm to improve the local search 局部搜索算法，改进局部搜索

14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings. Pub Date : 2002-11-04 DOI: 10.1109/TAI.2002.1180836

M. Tounsi, P. David

引用次数: 2

DSatz: a directional SAT solver for planning DSatz：用于规划的定向 SAT 求解器

14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings. Pub Date : 2002-11-04 DOI: 10.1109/TAI.2002.1180805

M. Iwen, A. Mali

{"title":"DSatz: a directional SAT solver for planning","authors":"M. Iwen, A. Mali","doi":"10.1109/TAI.2002.1180805","DOIUrl":"https://doi.org/10.1109/TAI.2002.1180805","url":null,"abstract":"SAT-based planners have been characterized as disjunctive planners that maintain a compact representation of search space of action sequences. Several ideas from refinement planners (conjunctive planners) have been used to improve performance of SAT-based planners or get a better understanding of planning as SAT One important lesson from refinement planning is that backward search being goal directed can be more efficient than forward search. Another lesson is that bidirectional search is generally not efficient. This is because the forward and backward searches can miss each other Though effect of direction of plan refinement (forward, backward, bidirectional etc.) on efficiency of plan synthesis has been deeply investigated in refinement planning, the effect of directional solving of SAT encodings is not investigated in depth. We solved several propositional encodings of benchmark planning problems with a modified form (DSatz) of the systematic SAT solver Satz. DSatz offers 21 options for solving a SAT encoding of a planning problem, where the options are about assigning truth values to action and/or fluent variables in forward or backward or both directions, in an intermittent or non-intermittent style. Our investigation shows that backward search on plan encodings (assigning values to fluent variables first, starting with goal) is very inferior We also show bidirectional solving options and forward solving options turn out to be far more efficient than other solving options. Our empirical results show that the efficient systematic solver Satz which exploits variable dependencies call be significantly enhanced with use of our variable ordering heuristics which are also computationally very cheap to apply. Our main results are that directionality does matter in solving SAT encodings of planning problems and that certain directional solving options are superior to others.","PeriodicalId":197064,"journal":{"name":"14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings.","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129748022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

A neural-network approach to modeling and analysis 建模和分析的神经网络方法

14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings. Pub Date : 2002-11-04 DOI: 10.1109/TAI.2002.1180843

Chen-Yuan Chen, Cheng-Wu Chen, W. Chiang, Jing-Dong Hwang

引用次数: 0

Automated diagnosis of non-native English speaker's natural language 非英语母语者自然语言的自动诊断

14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings. Pub Date : 2002-11-04 DOI: 10.1109/TAI.2002.1180818

Richard Fox, Mari Bowden

引用次数: 7

Actions with duration and constraints: the ramification problem in temporal databases 具有持续时间和约束的操作:时态数据库中的分支问题

14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings. Pub Date : 2002-11-04 DOI: 10.1109/TAI.2002.1180791

N. Papadakis, D. Plexousakis

引用次数: 28

Mining association rules in text databases using multipass with inverted hashing and pruning 基于反向哈希和剪接的多通道文本数据库关联规则挖掘

14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings. Pub Date : 2002-11-04 DOI: 10.1109/TAI.2002.1180787

John D. Holt, S. M. Chung

引用次数: 10

Software quality classification modeling using the SPRINT decision tree algorithm 使用SPRINT决策树算法进行软件质量分类建模

14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings. Pub Date : 2002-11-04 DOI: 10.1109/TAI.2002.1180826

T. Khoshgoftaar, Naeem Seliya

{"title":"Software quality classification modeling using the SPRINT decision tree algorithm","authors":"T. Khoshgoftaar, Naeem Seliya","doi":"10.1109/TAI.2002.1180826","DOIUrl":"https://doi.org/10.1109/TAI.2002.1180826","url":null,"abstract":"Predicting the quality of system modules prior to software testing and operations can benefit the software development team. Such a timely reliability estimation can be used to direct cost-effective quality improvement efforts to the high-risk modules. Tree-based software quality classification models based on software metrics are used to predict whether a software module is fault-prone or not fault-prone. They are white box quality estimation models with good accuracy, and are simple and easy to interpret. This paper presents an in-depth study of calibrating classification trees for software quality estimation using the SPRINT decision tree algorithm. Many classification algorithms have memory limitations including the requirement that data sets be memory resident. SPRINT removes all of these limitations and provides a fast and scalable analysis. It is an extension of a commonly used decision tree algorithm, CART, and provides a unique tree-pruning technique based on the minimum description length (MDL) principle. Combining the MDL pruning technique and the modified classification algorithm, SPRINT yields classification trees with useful prediction accuracy. The case study used comprises of software metrics and fault data collected over four releases from a very large telecommunications system. It is observed that classification trees built by SPRINT are more balanced and demonstrate better stability in comparison to those built by CART.","PeriodicalId":197064,"journal":{"name":"14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings.","volume":"381 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132877744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 84

Protein secondary structure prediction with Bayesian learning method 基于贝叶斯学习方法的蛋白质二级结构预测

14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings. Pub Date : 2002-11-04 DOI: 10.1109/TAI.2002.1180812

Peng Wang, Du Zhang

引用次数: 4