Fuzzy Hybrid Computing in Construction Engineering and Management最新文献_第2页

Crane Guidance Gesture Recognition using Fuzzy Logic and Kalman Filtering 基于模糊逻辑和卡尔曼滤波的起重机制导手势识别

Fuzzy Hybrid Computing in Construction Engineering and Management Pub Date : 2018-10-04 DOI: 10.1108/978-1-78743-868-220181013

Xin Wang, Chris Gordon

引用次数: 0

Modelling Construction Management Problems with Fuzzy Cognitive Maps 用模糊认知图建模施工管理问题

Fuzzy Hybrid Computing in Construction Engineering and Management Pub Date : 2018-10-04 DOI: 10.1108/978-1-78743-868-220181012

Denise M. Case, T. Blackburn, C. Stylios

{"title":"Modelling Construction Management Problems with Fuzzy Cognitive Maps","authors":"Denise M. Case, T. Blackburn, C. Stylios","doi":"10.1108/978-1-78743-868-220181012","DOIUrl":"https://doi.org/10.1108/978-1-78743-868-220181012","url":null,"abstract":"Abstract \u0000This chapter discusses the application of fuzzy cognitive map (FCM) modelling to construction management (CM) challenges and problems. It focuses on the critical issue of managing the complexity and uncertainty inherent in CM by providing a new intelligent layer that enhances classical approaches to construction modelling and management. It investigates how the myriad types of internal and external factors affecting the feasibility and performance of construction projects can be modelled using a fuzzy hybrid method that explores the complex relationships among many contributing factors and assesses and evaluates their impacts on past and future projects. This chapter proposes a hybrid modelling approach in the traditional context of cost, schedule and risk management and describes how augmenting and enhancing existing state-of-the-art tools and processes in CM can assist construction managers. This chapter provides a background on the theory of FCMs, presents foundational and current research, and explains how to apply this approach in the CM domain. This chapter also provides a detailed description of how to develop, modify and employ interactive models to specific CM challenges and problems. It includes a customisable, interactive base model and demonstrates how the model has been applied to specific CM events and issues. Examples are presented that highlight the interplay between project-specific goals and characteristics and the way these impact the interrelated and often opposing triad of cost, schedule and risk. The presented examples and practical applications make this state-of-the-art approach useful to both academic and industry practitioners.","PeriodicalId":301967,"journal":{"name":"Fuzzy Hybrid Computing in Construction Engineering and Management","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133181903","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: 5

Fuzzy Arithmetic Operations: Theory and Applications in Construction Engineering and Management 模糊算术运算:理论及其在建筑工程与管理中的应用

Fuzzy Hybrid Computing in Construction Engineering and Management Pub Date : 2018-10-04 DOI: 10.1108/978-1-78743-868-220181003

N. G. Seresht, A. Fayek

{"title":"Fuzzy Arithmetic Operations: Theory and Applications in Construction Engineering and Management","authors":"N. G. Seresht, A. Fayek","doi":"10.1108/978-1-78743-868-220181003","DOIUrl":"https://doi.org/10.1108/978-1-78743-868-220181003","url":null,"abstract":"Abstract \u0000Fuzzy numbers are often used to represent non-probabilistic uncertainty in engineering, decision-making and control system applications. In these applications, fuzzy arithmetic operations are frequently used for solving mathematical equations that contain fuzzy numbers. There are two approaches proposed in the literature for implementing fuzzy arithmetic operations: the α-cut approach and the extension principle approach using different t-norms. Computational methods for the implementation of fuzzy arithmetic operations in different applications are also proposed in the literature; these methods are usually developed for specific types of fuzzy numbers. This chapter discusses existing methods for implementing fuzzy arithmetic on triangular fuzzy numbers using both the α-cut approach and the extension principle approach using the min and drastic product t-norms. This chapter also presents novel computational methods for the implementation of fuzzy arithmetic on triangular fuzzy numbers using algebraic product and bounded difference t-norms. The applicability of the α-cut approach is limited because it tends to overestimate uncertainty, and the extension principle approach using the drastic product t-norm produces fuzzy numbers that are highly sensitive to changes in the input fuzzy numbers. The novel computational methods proposed in this chapter for implementing fuzzy arithmetic using algebraic product and bounded difference t-norms contribute to a more effective use of fuzzy arithmetic in construction applications. This chapter also presents an example of the application of fuzzy arithmetic operations to a construction problem. In addition, it discusses the effects of using different approaches for implementing fuzzy arithmetic operations in solving practical construction problems.","PeriodicalId":301967,"journal":{"name":"Fuzzy Hybrid Computing in Construction Engineering and Management","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123930995","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

Index 指数

Fuzzy Hybrid Computing in Construction Engineering and Management Pub Date : 2018-10-04 DOI: 10.1108/978-1-78743-868-220181014

引用次数: 0