LSP suitability maps

In this paper, we propose the concept of logically aggregated geographic suitability maps (LSP-maps). The goal of LSP-maps is to provide specialized maps of the suitability degree of a selected geographic region for a specific purpose. There is a wide spectrum of purposes which include suitability for industrial development, agriculture, housing, education, recreation, etc. Our goals are to specify the main concepts of LSP-maps development and to identify some of the potential application areas. Our approach is based on soft computing with partial truth and graded logic functions within the framework of the LSP method.     

Multicriteria decision-making using Archimedean aggregation operators in Pythagorean hesitant fuzzy environment

In multicriteria decision-making (MCDM), the existing aggregation operators are mostly based on algebraic t-conorm and t-norm. But, Archimedean t-conorms and t-norms are the generalized forms of t-conorms and t-norms which include algebraic, Einstein, Hamacher, Frank, and other types of t-conorms and t-norms. From that view point, in this paper the concepts of Archimedean t-conorm and t-norm are introduced to aggregate Pythagorean hesitant fuzzy information. Some new operational laws for Pythagorean hesitant fuzzy numbers based on Archimedean t-conorm and t-norm have been proposed. Using those operational laws, Archimedean t-conorm and t-norm-based Pythagorean hesitant fuzzy weighted averaging operator and weighted geometric operator are developed. Some of their desirable properties have also been investigated. Afterwards, these operators are applied to solve MCDM problems in Pythagorean hesitant fuzzy environment. The developed Archimedean aggregation operators are also applicable in Pythagorean fuzzy contexts also. To demonstrate the validity, practicality, and effectiveness of the proposed method, a practical problem is considered, solved, and compared with other existing method.     

Relating logic programs via program maps

This paper presents a mathematical theory underlying a systematic method for constructingProlog programs calledstepwise enhancement. Stepwise enhancement dictates building a program starting with askeleton program which constitutes the basic control flow for the problem to be solved, and adding extra computations to the skeleton program by using well-understood programming techniques. Each extra computation can be developed independently, and the separate enhancements combined to produce the final program. While intuition and motivation have focused onProlog, the methods are applicable to logic programming languages more generally. The central concept in our mathematical theory for stepwise enhancement is that of a program map between two logic programs. Our definition of a program map from an enhancement to its skeleton guarantees the lifting of computations, the essence of the enhancement methodology. In this paper, we give definitions of program map and extensions, show that the definitions preserve the property of computations lifting, give examples of extensions and programming techniques which generate them, and point to directions for future work.     

On the logic of preference and judgment aggregation

Agents that must reach agreements with other agents need to reason about how their preferences, judgments, and beliefs might be aggregated with those of others by the social choice mechanisms that govern their interactions. The emerging field of judgment aggregation studies aggregation from a logical perspective, and considers how multiple sets of logical formulae can be aggregated to a single consistent set. As a special case, judgment aggregation can be seen to subsume classical preference aggregation. We present a modal logic that is intended to support reasoning about judgment aggregation scenarios (and hence, as a special case, about preference aggregation): the logical language is interpreted directly in judgment aggregation rules. We present a sound and complete axiomatisation. We show that the logic can express aggregation rules such as majority voting; rule properties such as independence; and results such as the discursive paradox, Arrow’s theorem and Condorcet’s paradox—which are derivable as formal theorems of the logic. The logic is parameterised in such a way that it can be used as a general framework for comparing the logical properties of different types of aggregation—including classical preference aggregation. As a case study we present a logical study of, including a formal proof of, the neutrality lemma, the main ingredient in a well-known proof of Arrow’s theorem.     

Evidence aggregation networks for fuzzy logic inference

Fuzzy logic has been applied in many engineering disciplines. The problem of fuzzy logic inference is investigated as a question of aggregation of evidence. A fixed network architecture employing general fuzzy unions and intersections is proposed as a mechanism to implement fuzzy logic inference. It is shown that these networks possess desirable theoretical properties. Networks based on parameterized families of operators (such as Yager's union and intersection) have extra predictable properties and admit a training algorithm which produces sharper inference results than were earlier obtained. Simulation studies corroborate the theoretical properties.     

Multicriteria decision making with 2‐dimension linguistic aggregation techniques

In this paper, we represent evaluation information by 2‐dimension linguistic labels so as to avoid biased results and achieve high accuracy in multicriteria decision making. We analyze the relationship between a 2‐dimension linguistic label and a common linguistic label, and then quantify a certain 2‐dimension linguistic label by using a generalized triangular fuzzy number (TFN). On the basis of the mapping function from 2‐dimension linguistic labels to the corresponding generalized TFNs and its inverse function, we develop a 2‐dimension linguistic weighted averaging (2DLWA) operator and a 2‐dimension linguistic ordered weighted averaging (2DLOWA) operator. Furthermore, we verify the feasibility of the 2DLWA and 2DLOWA operators by discussing their properties and investigating their applications to produce reliable decision results in multicriteria decision making under linguistic evaluations. Finally, an example of selecting the outstanding postgraduate dissertation(s) is used to illustrate the practicability and validity of these two 2‐dimension linguistic aggregation techniques. © 2012 Wiley Periodicals, Inc.     

Multicriteria fuzzy decision-making methods based on intuitionistic fuzzy sets

In this paper, a new method for handling multicriteria fuzzy decision-making problems based on intuitionistic fuzzy sets is presented. The proposed method allows the degrees of satisfiability and non-satisfiability of each alternative with respect to a set of criteria to be represented by intuitionistic fuzzy sets, respectively. Furthermore, the proposed method allows the decision-maker to assign the degrees of membership and non-membership of the criteria to the fuzzy concept “importance.” The method proposed here can provide a useful way to efficiently help the decision-maker to make his decision.     

Filtering multilingual Web content using fuzzy logic and self-organizing maps

Effective multilingual information filtering is required to alleviate users burden of information overload resulting from the increasing flood of multilingual textual content available extensively over the World-Wide Web. This paper proposes a content-based self-organizing approach to multilingual information filtering using fuzzy logic and the self-organizing map. This approach screens and evaluates multilingual documents based on their semantic contents. Correlated multilingual documents are disseminated according to their corresponding themes or topics, thus enabling language-independent content-based information access efficiently and effectively. A Web-based multilingual online news-filtering system is developed to illustrate how the approach works.     

A general approach to rule aggregation in fuzzy logic control

We look at the representation and aggregation of individual rules in the fuzzy logic control system. Two extreme paradigms for rule representation are introduced, the Mamdani model and the logical model. We look at the characteristics of these approaches. We then combine these two approaches to get a general model for the representation of rules. From this general formulation we obtain two soft classes of rules aggregation, or-like and and-like aggregations.     

Effective problem solving through fuzzy logic knowledge bases aggregation

Cooperative problem solving has attracted great interest in the research community. A number of nodes can cooperate to reach a common goal which is the solution to a specific problem. Through a team effort, nodes try to achieve the best possible result. Each node undertakes the responsibility to fulfill a specific task (part of a complex plan towards the solution of the problem) and return the final outcome to a coordinator. The coordinator assigns tasks to nodes and, accordingly, collects the results. In this paper, we propose the adoption of fuzzy logic (FL) in the decision making process of each node. Nodes adopt the provided (by the coordinator) FL knowledge base that indicates the appropriate actions during the problem solving process. This knowledge base is updated during the execution of the assigned task to be fully aligned with the environment characteristics. Partial knowledge bases experienced by the nodes are sent back to the coordinator and are aggregated to generate a ‘global’ knowledge base that incorporates the experience retrieved by the team. We describe the aggregation process and propose two models: the first adopts the immediate distribution of the aggregated FL rule base to the active nodes and the second indicates the future use of the aggregated FL rule base. Our evaluation involves the realization of the proposed framework in a specific research domain as well as numerical results retrieved by a large number of simulations. Our results show that there is a trade-off between the two proposed models concerning the quality of the final solution and the time required to retrieve the final outcome.     

Determination of travertine provenance from ancient buildings using self-organizing maps and fuzzy logic

This work is focused on determining provenance of travertine stones employed in the construction of some important monuments in Umbria (Italy) using two systems that use concepts and algorithms inherent to Artificial Intelligence: Kohonen self-organizing maps and fuzzy logic. The two systems have been applied to travertine samples belonging to quarries known to be sites of excavation from ancient times and monuments. Tests on quarry samples show a good discriminative power of both methods to recognize the exact provenance of most samples. The application of the systems to monument samples show that most of employed travertine stones were quarried from outcrops occurring in areas close to the towns where monuments have been erected. Results are in good agreement with historical data.     

The Hellinger distance in Multicriteria Decision Making: An illustration to the TOPSIS and TODIM methods

Due to the difficulty in some situations of expressing the ratings of alternatives as exact real numbers, many well-known methods to support Multicriteria Decision Making (MCDM) have been extended to compute with many types of information. This paper focuses on the information represented as probability distribution. Many of the methods that deal with probability distribution use the concept of stochastic dominance, which imposes very strong restrictions to differentiate two probability distributions, or uses the probability distributions to obtain a quantity that will be used to rank the alternatives. This paper brings the Hellinger distance concept to the MCDM context to assist the models to deal with probability distributions in a direct way without any transformation. Transformations in the data or summary quantities may miss represent the original information. For direct comparisons among probability distributions we use the stochastic dominance degree (SDD). We illustrate how simple it can be to adapt the existing methods to deal with probability distributions through the Hellinger distance and SDD by adapting the TOPSIS and TODIM (an acronym in Portuguese of Interactive and Multicriteria Decision Making) methods.     

启发式方法生成命题逻辑可读证明

探讨了自动生成命题逻辑系统R的可读证明.采用试探法和自然推理法分别从前推和后推模拟人类思维求证,试探法根据推理规则将待证公式反向分解,自然推理法从假设出发根据推理规则生成新的公式.两种方法都实现了相干命题逻辑系统R的可读证明,并结合实现了混合证明.试探法和自然推理法是生成可读证明的有效方法,前推和后推两种思维方法也适用于其他逻辑系统的自动证明.     

Investigating measurement scales and aggregation methods in SPICE assessment method

ContextThis study identified three issues in SPICE (Software Process Assessment and Capability dEtermination) assessment method based on ISO/IEC 15504-2 (Performing an assessment). The issues include a lack of a measurement scale for characterizing the extent to which an outcome (practice) is achieved (implemented) and two shortcomings of the aggregation methods in order to generate a process attribute (PA) rating. Such issues may be weaknesses to the needs of retaining consistent assessment results comparable within and across assessed organizations.ObjectiveThe purpose of this study is to identify issues, such as the measurement scale and aggregation methods, in SPICE assessment methods and to provide candidate solutions based on measurement theories, while the rating scales of the current PA and capability are retained.MethodFor those purposes, the present study reviews scale types based on a measurement theory and uses the reflective and formative measurement models in order to find the relationships between PAs and practices. Composite measure development methods that are dependent on the relationships are then proposed on the basis of appropriate aggregation methods by using multiple attribute decision making (MADM) methods.ResultsSix candidate solutions are presented along with their strengths and weaknesses based on practical and theoretical perspectives. Two examples are given to illustrate and interpret six candidate solutions for the issues identified. By applying six candidate solutions to the examples shows that the measurement scale and the aggregation methods influence the PA rating.ConclusionThe process community, including the SPICE standardization group, can initiate discussions in order to determine the measurement scale and the aggregation methods with our six candidate solutions. The rationale and methods addressed in this study can also be applied to other domains in order to derive a composite (aggregate) value or rating.     

车站联锁进路控制逻辑的形式化方法

基于计算机联锁系统是一个对列车行驶系统提供安全条件的系统,车站联锁系统是保证车站行车安全和提高运输效率的典型安全苛求性系统。以形式化 方法Event-B为基础,引入角色Agent对联锁系统进行规范定义,通过智能体与Event-B的建模和验证,构造了车站联锁进路控制逻辑形式化验证模型,并进行 了形式化规范和推理,该模型在RODIN平台上进行验证,通过实例验证,满足了计算机联锁系统的安全需求。     

Adaptive aggregation methods for infinite horizon dynamicprogramming

A class of iterative aggregation algorithms for solving infinite horizon dynamic programming problems is proposed. The idea is to interject aggregation iterations in the course of the usual successive approximation method. An important feature that sets this method apart from earlier ones is that the aggregate groups of states change adaptively from one aggregation iteration to the next, depending on the progress of the computation. This allows acceleration of convergence in difficult problems involving multiple-ergodic classes for which methods using fixed groups of aggregate states are ineffective. No knowledge of special problem structure is utilized by the algorithms     

Comparison of OR and AI methods in discrete manufacturing using fuzzy logic

Since 1950s the techniques of Operations Research (OR) and Optimization have been utilized to increase the efficiency of the production systems. With the widespread use of computers, it has even become easier to deal with industrial problems. However the complexity of the problems still reveals the difficulty in providing solutions. The use of artificial intelligence (AI) seems to attract the attention of the researcher to overcome to the difficulties. This has already been realized with several successful applications. In this study, the use of AI and OR techniques is compared using fuzzy logic. The progress of manufacturing systems, characteristics of production processes, system managements and system behavior are taken into account. The study is focussed on only discrete manufacturing.