Fuzzy Sets, Fuzzy Logic and Their Applications

The present book contains 20 articles collected from amongst the 53 total submitted manuscripts for the Special Issue “Fuzzy Sets, Fuzzy Loigic and Their Applications” of the MDPI journal Mathematics. The articles, which appear in the book in the series in which they were accepted, published in Volumes 7 (2019) and 8 (2020) of the journal, cover a wide range of topics connected to the theory and applications of fuzzy systems and their extensions and generalizations. This range includes, among others, management of the uncertainty in a fuzzy environment; fuzzy assessment methods of human-machine performance; fuzzy graphs; fuzzy topological and convergence spaces; bipolar fuzzy relations; type-2 fuzzy; and intuitionistic, interval-valued, complex, picture, and Pythagorean fuzzy sets, soft sets and algebras, etc. The applications presented are oriented to finance, fuzzy analytic hierarchy, green supply chain industries, smart health practice, and hotel selection. This wide range of topics makes the book interesting for all those working in the wider area of Fuzzy sets and systems and of fuzzy logic and for those who have the proper mathematical background who wish to become familiar with recent advances in fuzzy mathematics, which has entered to almost all sectors of human life and activity

Quantifying the Impact of Change Orders on Construction Labor Productivity Using System Dynamics

Researchers and industry practitioners agree that changes are unavoidable in construction projects and may become troublesome if poorly managed. One of the root causes of sub-optimal productivity in construction projects is the number and impact of changes introduced to the initial scope of work during the course of project execution. In labor-intensive construction projects, labor costs represent a substantial percentage of the total project budget. Understanding labor productivity is essential to project success. If productivity is impacted by any reasons such as extensive changes or poor managerial policies, labor costs will increase over and above planned cost. The true challenge of change management is having a comprehensive understanding of change impacts and how these impacts can be reduced or prevented before they cascade forming serious problems. This thesis proposes a change management framework that project teams can use to quantify labor productivity losses due to change orders and managerial policies across all phases of construction projects. The proposed framework has three models; fuzzy risk-based change management, AI baseline-productivity estimating, and system dynamics to illustrate cause-impact relationships. These models were developed in five stages. In the first stage, the fuzzy risk-based change management (FRCM) model was developed to prioritize change orders in a way that only essential change orders can be targeted. In this stage, Fuzzy Analytic Hierarchy Process (F-AHP) and Hierarchical Fuzzy Inference System are utilized to calculate relative weights of the factors considered and generate a score for each contemplated change. In the second stage, baseline productivity model was developed considering a set of environmental and operational variables. In this step, various techniques were used including Stepwise, Best Subset, Evolutionary Polynomial Regression (EPR), General Regression Neural Network (GRNN), Artificial Neural Network (ANN), Radial Basis Function Neural Network (RBFNN), and Adaptive Neuro Fuzzy Inference System (ANFIS) in order to compare results and choose the best method for producing that estimate. The selected method was then used in the development of a novel AI model for estimating labor productivity. The developed AI model is based on Radial Basis Function Neural Network (RBFNN) after enhancing it by raw dataset preprocessing and Particle Swarm Optimization (PSO) to extract significant dataset features for better generalization. The model, named PSO-RBFNN, was selected over other techniques based on its statistical performance and was used to estimate the baseline productivity values used as the initial value in the developed system dynamics (SD) model. In the fourth stage, a novel SD model was developed to examine the impact of change orders and different managerial decisions in response to imposed change orders on the expected productivity during the lifecycle of a project. In other words, the SD model is used to quantify the impact of change orders and related managerial decisions on excepted productivity. The SD model boundary was defined by clustering key variables into three categories: exogenous, endogenous, and excluded. The relationships among these key variables were extracted from the literature and experts in this domain. A holistic causal loop diagram was then developed to illustrate the interaction among various variables. In the final stage, the developed computational framework and its models were verified and validated through a real case study and the results show that the developed SD model addresses various consequences derived from a change in combination with the major environmental and operational variables of the project. It allows for the identification and quantification of the cumulative impact of change orders on labor productivity in a timely manner to facilitate the decision-making process. The developed framework can be used during the development and execution phases of a project. The findings are expected to enhance the assessment of change orders, facilitate the quantification of productivity losses in construction projects, and help to perform critical analysis of the impact of various scope change internal and external variables on project time and cost

Dynamic Analysis of Cracked Rotor in Viscous Medium and its Crack Diagnosis Using Intelligent Techniques

Fatigue cracks have high potential to cause catastrophic failures in the rotor which can lead to catastrophic failure if undetected properly and in time. This fault may interrupt smooth, effective and efficient operation and performance of the machines. Thereby the importance of identification of crack in the rotor is not only for leading safe operation but also to prevent the loss of economy and lives.The condition monitoring of the engineering systems is attracted by the researchers and scientists very much to invent the automated fault diagnosis mechanism using the change in dynamic response before and after damage. When the rotor with transverse crack immersed in the viscous fluid, analysis of cracked rotor is difficult and complex. The analysis of cracked rotor partially submerged in the viscous fluid is widely used in various engineering systems such as long spinning shaft used drilling the seabed for the extracting the oil, high-speed turbine rotors, and analysis of centrifuges in a fluid medium. Therefore, dynamic analysis of cracked rotor partially submerged in the viscous medium have been presented in the current study. The theoretical analysis has been performed to measure the vibration signatures (Natural Frequencies and Amplitude) of multiple cracked mild steel rotor partially submerged in the viscous medium. The presence of the crack in rotor generates an additional flexibility. That is evaluated by strain energy release rate given by linear fracture mechanics. The additional flexibility alters the dynamic characteristics of cracked rotor in a viscous fluid. The local stiffness matrix has been calculated by the inverse of local dimensionless compliance matrix. The finite element analysis has been carried out to measure the vibration characteristics of cracked rotor partially submerged in the viscous medium using commercially available finite element software package ANSYS. It is observed from the current analysis, the various factors such as the viscosity of fluid, depth and position of the cracks affect the performance of the rotor and effectiveness of crack detection techniques. Various Artificial Intelligent (AI) techniques such as fuzzy logic, hybrid BPNN-RBFNN neural network, MANFIS and hybrid fuzzy-rule base controller based multiple faults diagnosis systems are developed using the dynamic response of rotating cracked rotor in a viscous medium to monitor the presence of crack. Experiments have been conducted to authenticate the performance and accuracy of proposed methods. Good agreement is observed between the results