A fuzzy constraint-based approach to data reconciliation in material flow analysis

Association analysis of amino acids in molecular sequences can reveal crucial information and knowledge for understanding structure, function and interaction of proteins. The traditional methods of association rule mining like apriori, F-P Growth etc. fail to generate appropriate patterns due to inherent uncertainty present in data. The uncertainty in sequence data caused by variation in the length of sequences and lack of parameterization lead to under prediction and over prediction of the results. In this paper an attempt has been made to develop a soft set based approach for mining fuzzy association patterns in peptide sequences of dengue virus. The fuzzy set approach is employed to incorporate the degree of relationships among amino acids due to variation in length of the sequences. The soft set approach is employed to incorporate the relationship of parameters with amino acid association patterns. The 12,581 sequences of dengue virus are downloaded from NCBI and screened for redundancy to obtain non redundant 6995 sequences. The amino acid associations are explored and analyzed using soft fuzzy approach. Also the results obtained by soft fuzzy approach are compared with the results obtained individually by ordinary, fuzzy and soft set approaches. The soft fuzzy approach is able to overcome the issue of under prediction and over prediction of the results obtained by other approaches. Also the interesting association rules have been generated to predict the structure and physico chemical properties of the peptide sequences.

Material flow networks are a specific technique for material flow analysis. Software tools based on this method have been used by many companies to analyze and improve complex production systems. While their intuitive modeling approach strongly enhances the identification of optimization potentials, automatic model optimization is not yet possible. The KOMSA project has closed this important methodological and instrumental gap. This article presents the developed prototype of a material flow‐based optimization tool. We provide numerical results on the convergence of the implemented optimization algorithms. The added value of integrating optimization with material flow analysis is illustrated by applying the software tool to a real optimization problem from the waste industry.

The text explains that the fuzzy approaches have the objective to bring the decision process in planning closer to the decision maker, by allowing him to understand better the diversity of aspects that must be considered in planning decisions and helping the decision process while keeping as much information as possible, represented in the definition of fuzzy sets. The paper shows that the qualitative aspects of uncertainty, risk and decision making may be adequately modeled with a fuzzy set approach. It could help the decision maker guiding him towards a decision that takes in account uncertainty in the future, the multiple criteria evaluation of plans, as well as hedging policies.

Confidence sets are generally interpreted in terms of replications of an experiment. However, this interpretation is only valid before observing the sample. After observing the sample, any confidence sets have probability zero or one to contain the parameter value. In this paper, we provide a confidence set analysis for an observed sample based on fuzzy set theory by using the concept of membership functions. We show that the traditional ad hoc thresholds (the confidence and significance levels) can be attained from a general membership function. The applicability of the newly proposed theory is demonstrated by using well-known examples from the statistical literature and an application in the context of contingency tables.

In Calcutta metro, railways, roads and waterways are available to provide mass transport services. An attempt has been made to use non-conventional abstract mathematical theory to solve the multimodal mass transport system. Fuzzy functions have been used as an analytical tool, to express the satisfaction level of attributes as viewed by different interest groups. The central concept of fuzzy set theory is the membership function which represents numerically the degree to which an element belongs to a set. This function takes values from zero to one. For synthesizing information, rating matrices have been constructed with different alternative modes as columns against various attributes/factors as rows. Each rating matrix represents the evaluation made by a respective interest group. Having identified the corridor and selective modal characteristics, the preferred mode may be chosen by this method. Additionally, when the need for introducing some new mode or increasing the services of some old mode are felt, this procedure may be used as a simplified tool.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Using Material Flow Analysis for Sustainable Materials Management

A review of a series of effective methods in urban metabolism: Material flow, ecological network and factor analysis

E-waste flow among selected institutions of higher learning using material flow analysis model

Tolerance-based intuitionistic fuzzy-rough set approach for attribute reduction

Based on the combination of the U.S. economic input-output table and the stocks and flows framework for characterizing anthropogenic metal cycles, this study presents a methodology for building material flow networks of bulk metals in the U.S. economy and applies it to aluminum. The results, which we term the Input-Output Material Flow Networks (IO-MFNs), achieve a complete picture of aluminum flow in the entire U.S. economy and for any chosen industrial sector (illustrated for the Automobile Manufacturing sector). The results are compared with information from our former study on U.S. aluminum stocks and flows to demonstrate the robustness and value of this new methodology. We find that the IO-MFN approach has the following advantages: (1) it helps to uncover the network of material flows in the manufacturing stage in the life cycle of metals; (2) it provides a method that may be less time-consuming but more complete and accurate in estimating new scrap generation, process loss, domestic final demand, and trade of final products of metals, than existing material flow analysis approaches; and, most importantly, (3) it enables the analysis of the material flows of metals in the U.S. economy from a network perspective, rather than merely that of a life cycle chain.

Eco-balance is the basis for the assessing production impact on the environment. Eco-balancing is divided into four phases: goal and scope definition, inventory analysis, impact assessment, interpretation. However, during the creation and evaluation of material flow networks some defects appear which inhibit or make it more difficult to establish realistic statements towards the environmental impact. In order to make a reliable statement about the environmental impact with the help of eco-balance it is necessary to consider all material and energy flows. This chapter gives an overview of the classification of defects in material flow networks. After the classification of data defects the causes of these defects are discussed. In order to resolve the causes of defects some solutions will be presented using the advantages of Petri nets and the application of Fuzzy sets and Rough sets to the Petri nets.

Automatically determine the membership function based on the maximum entropy principle

Lot output time prediction is a critical task to a wafer fab (fabrication plant). Traditional studies are focused on prediction accuracy and efficiency. Another performance measure that is as important but has been ignored in traditional studies is the achievability of an output time forecast, which is defined as the possibility that the fabrication on a wafer lot can be finished in time before the output time forecast. Theoretically, if a probability distribution can be obtained for the output time forecast, then the achievability can be evaluated with the cumulative probability of the probability distribution before the given date. However, there are many managerial actions that are more influential to the achievability. For this reason, a fuzzy set approach is proposed for evaluating the achievability of the output time forecast. The fuzzy set approach is composed of two parts: a fuzzy back propagation network (FBPN) and a set of fuzzy inference rules (FIRs). An example is used to demonstrate the applicability of the proposed methodology.

• Propose novel behavioral membership functions within the fuzzy goal programming approach. • Model decision-makers’ behavioral aspects and risk perceptions. • Develop a behavior-based fuzzy goal programming approach. • Enhance utility functions within the fuzzy goal programming methodology. • Demonstrate applicability and efficacy through a venture capital investment problem. A relevant extension of traditional goal programming (GP), fuzzy goal programming (FGP) can handle uncertainty and imprecision in multi-objective optimization problems. Based on fuzzy set theory, the notion of membership functions has been introduced to consider the fuzziness related to objectives and constraints. These membership functions are mainly intended for fuzziness in the GP rather than modeling the decision-maker's (DM's) preferences and his/her attitude toward risk in the decision-making process. In the satisfying philosophy of FGP, little attention has been given to how preferences evolve in terms of the behavior of the decision-maker (DM) and how these preferences may affect decisions in risky scenarios. To address this issue, we suggest novel behavioral-type utility functions for the FGP approach by introducing the concept of behavioral membership functions. This concept offers an innovative procedure for simulating the DM's behavioral preferences in the FGP approach. First, two main categories of objectives in relation to the DM's behavioral preferences are distinguished in this work. A risk aversion parameter is integrated into membership functions according to the nature of each objective type, obtaining the so-called behavioral membership functions. A behavioral FGP approach is subsequently formulated. Finally, an illustrative example of venture capital investments, a sensitivity analysis, and comparisons with other FGP approaches are provided to demonstrate the validity and practicality of our proposed approach.

SummaryThis article is the first of a two‐part series that describes and compares the essential features of nine existing “physical economy” approaches for quantifying the material demands of the human economy upon the natural environment. A range of material flow analysis (MFA) and related techniques is assessed and compared in terms of several major dimensions. These include the system boundary identification for material flow sources, extents, and the key socioinstitutional entities containing relevant driving forces, as well as the nature and detailing of system components and flow interconnections, and the comprehensiveness and types of flows and materials covered.Shared conceptual themes of a new wave of physical economy approaches are described with a brief overview of the potential applications of this broad family of methodologies. The evolving and somewhat controversial nature of the characteristics and role that define MFA is examined. This review suggests the need to specify whether MFA is a general metabolic flow measurement procedure that can be applied from micro to macrolevels of economic activity, or a more specific methodology aimed primarily at economy‐wide analyses that “map” the material relations between society and nature. Some alternative options for classifying MFA are introduced for discussion before a more detailed comparative summary of the key methodological features of each approach in the second part of this two‐part article.The review is presented (1) as a reference and resource for the increasing number of policy makers and practitioners involved in industrial ecology and the evaluation of the material basis of economies and the formulation of eco‐efficiency strategies, and (2) to provoke discussion and ongoing dialogue to clarify the many existing areas of discordance in environmental accounting related to material flows, and help consolidate the methodological basis and application of MFA.