Different aspects of supporting group consensus reaching process under fuzziness

In this paper we present human-consistent approach of multi-model consensus reaching process supporting by group decision support systems. We consider the idea developed by Kacprzyk and Zadrożny [9, 10, 12] which is related to the “soft” consensus, and where the core of the system is based on fuzzy logic. Essentially, we attempt to stress the multi-model architecture of considering system and distinguish several aspects, i.e. model of agent, model of moderator, model of consensus achievement. Moreover, we present a novel concept based on fair consensus as a meaningful point of further development

Fuzzy querying: issues and perspectives

summary:The term query is widely used in the database as well as information retrieval communities. Basically, a query against a collection of information items (to be called later, for brevity, an information source) provides a formal description of the items of interest to the user posing this query. A source of information is meant here very generally. It may take the form of an archive of multimedia or textual documents, a database, or a knowledge base. In the three previous examples the information items are documents, records (rows in relational data model) and facts, respectively. In order to manage and access an information source, an appropriate system is defined which makes it possible to store, represent and retrieve information items by means of a formal query language. Information systems that make it possible to manage information items previously mentioned are information retrieval systems, data base management systems and knowledge based systems, respectively. Query languages of these systems usually refer to some features of entities represented by the items stored in an information source, e. g., keywords (index terms) in textual documents (documents archive), attributes (database) or arguments of facts (knowledge base). Thus, basically, a query may be seen as a set of selection conditions that should be met by an information item (its features) to be qualified as relevant with respect to the query. On the other hand, the query processing itself may be seen as consisting mainly of matching a query against the items of the information source. This process may be essentially more complex, as, e. g., in the case of knowledge bases where we deal with a whole chain of matching within the reasoning process. Often, a user faces the problem of how to express her or his information requirements in a formal query language supported by a given information system interface. These formal languages usually require a crisp (precise, unambiguous) specification of a query, while, for human beings, a query is best expressed in terms of a natural language – a very powerful, but ambiguous and imprecise medium. Thus, adding some flexibility to traditional querying systems seems to be a critical issue for enhancing their effectiveness and efficiency. In this paper, we discuss some recent advances and basic issues related to flexible querying based on the application of fuzzy logic. We focus on two areas corresponding to the type of information source under consideration, namely: information retrieval in which we primarily deal with archives of textual documents and database querying. Both areas share the same interest in fuzzy (linguistic) queries and flexible matching against items of information. However, they have also their specific features, and these are pointed out in the next sections. The third area, that of very broadly meant knowledge bases querying is dealt with in the paper by Peter Vojtáš, in this special issue. Specifically, the concept of matching, essential for querying, may be identified to some extent with the unification. In the mentioned paper, the issues related to the fuzzy unification are discussed. The matching of fuzzy concepts, from a slightly different perspective, is also the subject of the paper by Andrejková, in this issue. Another contribution relevant for the flexible querying of knowledge bases is the paper by Ch. Marsala, in this issue. Moreover, beside its application to querying itself, the concept of flexibility is usually extended to the representation of information to be queried. This is particularly evident in the area of information retrieval in which concepts of fuzzy logic fit very well into advanced indexing schemes for text documents. In case of database management systems, fuzzy logic based ideas have led to the development of imprecise/vague data representation models. These issues are also dealt with in the following sections. This paper is structured in two sections dealing with information retrieval and database querying, respectively. The paper is meant to provide a synthetic description of the research area of the papers appearing in this special issue of the Kybernetika. This issue is comprised of extended versions of selected papers presented at the session on fuzzy querying at the FSTA’2000 Conference held in Liptovský Mikuláš (Slovak Republic) in the winter of 2000. We refer to the other papers in this issue indicating their relevance for the topics discussed here

Contextual bipolarity and its quality criteria in bipolar linguistic summaries

Bipolar linguistic summaries of data are assumed to be an extension of the ‘classical’ linguistic summarization, a data mining technique revealing complex patterns present in data in a human consistent form. The extension proposal is based on the possibilistic interpretation of the ‘and possibly’ operator and introduced notion of context, which results in the introduction of the new ‘contextual and possibly’ operator. As the end user is expecting the most relevant summaries, ways of determining the quality of summary propositions (quality measures) needs to be developed. Here we focus on specific insights into the quality measures of proposed bipolar linguistic summaries of data and present some basic examples of their correctness and necessity of introduction

A novel text classification problem and its solution

A new text categorization problem is introduced. As in the classical problem, there is a set of documents and a set of categories. However, in addition to being assigned to a specific category, each document belongs to a certain sequence of documents, referred to as a case. It is assumed that all documents in the same case belong to the same category. An example may be a set of news articles. Their categories may be sport, politics, entertainment, etc. In each category there exist cases, i.e., sequences of documents describing, for example evolution of some events. The problem considered is how to classify a document to a proper category and a proper case within this category. In the paper we formalize the problem and discuss two approaches to its solution

Agri-food 4.0: A survey of the supply chains and technologies for the future agriculture

[EN] The term "Agri-Food 4.0" is an analogy to the term Industry 4.0; coming from the concept "agriculture 4.0". Since the origins of the industrial revolution, where the steam engines started the concept of Industry 1.0 and later the use of electricity upgraded the concept to Industry 2.0, the use of technologies generated a milestone in the industry revolution by addressing the Industry 3.0 concept. Hence, Industry 4.0, it is about including and integrating the latest developments based on digital technologies as well as the interoperability process across them. This allows enterprises to transmit real-time information in terms behaviour and performance. Therefore, the challenge is to maintain these complex networked structures efficiently linked and organised within the use of such technologies, especially to identify and satisfy supply chain stakeholders dynamic requirements. In this context, the agriculture domain is not an exception although it possesses some specialities depending from the domain. In fact, all agricultural machinery incorporates electronic controls and has entered to the digital age, enhancing their current performance. In addition, electronics, using sensors and drones, support the data collection of several agriculture key aspects, such as weather, geographical spatialization, animals and crops behaviours, as well as the entire farm life cycle. However, the use of the right methods and methodologies for enhancing agriculture supply chains performance is still a challenge, thus the concept of Industry 4.0 has evolved and adapted to agriculture 4.0 in order analyse the behaviours and performance in this specific domain. Thus, the question mark on how agriculture 4.0 support a better supply chain decision-making process, or how can help to save time to farmer to make effective decision based on objective data, remains open. Therefore, in this survey, a review of more than hundred papers on new technologies and the new available supply chains methods are analysed and contrasted to understand the future paths of the Agri-Food domain.Authors of this publication acknowledge the contribution of the Project 691249, RUC-APS "Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems" (www.ruc-aps.eu), funded by the European Union under their funding scheme H2020-MSCARISE-2015.Lezoche, M.; Hernández, JE.; Alemany Díaz, MDM.; Panetto, H.; Kacprzyk, J. (2020). Agri-food 4.0: A survey of the supply chains and technologies for the future agriculture. Computers in Industry. 117:1-15. https://doi.org/10.1016/j.compind.2020.103187S115117Ahumada, O., & Villalobos, J. R. (2009). Application of planning models in the agri-food supply chain: A review. 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Logarithmic aggregation operators and distance measures

The Hamming distance is a well‐known measure that is designed to provide insights into the similarity between two strings of information. In this study, we use the Hamming distance, the optimal deviation model, and the generalized ordered weighted logarithmic averaging (GOWLA) operator to develop the ordered weighted logarithmic averaging distance (OWLAD) operator and the generalized ordered weighted logarithmic averaging distance (GOWLAD) operator. The main advantage of these operators is the possibility of modeling a wider range of complex representations of problems under the assumption of an ideal possibility. We study the main properties, alternative formulations, and families of the proposed operators. We analyze multiple classical measures to characterize the weighting vector and propose alternatives to deal with the logarithmic properties of the operators. Furthermore, we present generalizations of the operators, which are obtained by studying their weighting vectors and the lambda parameter. Finally, an illustrative example regarding innovation project management measurement is proposed, in which a multi‐expert analysis and several of the newly introduced operators are utilized

A new measure of volatility using induced heavy moving averages

The volatility is a dispersion technique widely used in statistics and economics. This paper presents a new way to calculate volatility by using different extensions of the ordered weighted average (OWA) operator. This approach is called the induced heavy ordered weighted moving average (IHOWMA) volatility. The main advantage of this operator is that the classical volatility formula only takes into account the standard deviation and the average, while with this formulation it is possible to aggregate information according to the decision maker knowledge, expectations and attitude about the future. Some particular cases are also presented when the aggregation information process is applied only on the standard deviation or on the average. An example in three different exchange rates for 2016 are presented, these are for: USD/MXN, EUR/MXN and EUR/USD

Challenges and Solutions for Enhancing Agriculture Value Chain Decision-Making. A Short Review

Increasingly challenging global and environmental requirements have resulted in agricultural systems coming under increasing pressure to enhance their resilience capabilities. This in special to respond to the abrupt changes in resource quality, quantity and availability, especially during unexpected environmental circumstances, such as uncertain weather, pests and diseases, volatile market conditions and commodity prices. Therefore, integrated solutions are necessary to support the knowledge-management, collaborative ICT solution, risk management and regulation management across agriculture stakeholders. Therefore, and based on the on-going work under the H2020 RUC-APS project research network, this book chapter is oriented to contribute to agriculture value chain decision-making field to cover the current need on gathering a common understanding and appreciation of new trends in agriculture value chain, in special the multi-disciplinary challenges. For this, a short a literature review is conducted to summarise the main findings on real application and current research trends. This within the objective to propose an integrated framework based on better use of communication ways, standardised structures, development of training and awareness, regulation based initiatives and vertical Integration.Laboratorio de Investigación y Formación en Informática Avanzad