Fuzzy Logic

Badinelli R, Barile S, Ng I, Polese F, Saviano M, Di Nauta P (2012) Viable Service Systems and Decision Making in Service Management. Journal of Service Management 2011 Naples Forum on Service Special Issue, Issue 23, No 4, forthcoming

by Irene C L Ng

Purpose –This paper aims to highlight how systems thinking contributes to decision making in uncertain contexts that... more Purpose –This paper aims to highlight how systems thinking contributes to decision making in uncertain contexts that are characteristic of service systems. Based on the assumption that service systems face complex conditions, we posit that systems thinking may support the understanding of key issues in service management.

Design/methodology/approach – This paper proposes an interpretation of complexity in the context of service systems, which highlights the perspective change that occurs when a systems approach is adopted. The offered conceptual perspective is then brought to an operational level, in spite of the complexity of the decisions driving a viable system, by modeling a service system as a network of agents, resources, processes and decisions through the use of fuzzy logic. The paper reviews service management research streams, and takes a deeper look at the concepts of service systems and complex service systems. The paper then proceeds to discuss how systems thinking contributes to service management by proposing a systems interpretation of complexity.

Findings – Service management theories and models may be enhanced by integrating prevailing approaches, based on a quantitative and mechanistic view of service systems dynamics, with systems thinking-based meta-models that can be used in better understanding service exchanges. The findings of the paper also show how the integration of an engineering approach can be insightful to the understanding of service systems; adopting  a Viable Systems Approach (VSA) as a meta-model can be useful in fully comprehending market behavior in uncertain conditions.

Research limitations/implications – The paper introduces the VSA as a useful meta-model capable of better addressing decision making in service systems under conditions of complexity. The paper also proposes the adoption of fuzzy logic models to deal with  the vagueness and ambiguity that characterize complexity contexts.
Future research ought to investigate the analysis of complex phenomena, such as the service exchange, when adopting both the VSA and several operative models and constructs, in order to strengthen the observer’s capacity to understand reality.

Practical implications – The VSA’s contribution to decision making in the service exchange is clear when practitioners choose to adopt it as a meta-model that offers a terminological setting and general interpretative approaches. In this sense, practitioners may valorize this proposal to integrate its insights with operative models that support decision making in service systems and with a more powerful understanding of both the structural and operative levels characterizing their governance and development.


Originality/value – The originality of this paper lies in exploring the contribution of systems thinking,  in particular of the Viable Systems Approach (VSA), to service management and decision making.
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An Integrated Fuzzy AHP – Fuzzy TOPSIS Approach for AS/RS Selection

by ömür tosun

written with Hande E. AKTAN

System investment decision has a very crucial role in any company aiming for efficient manufacturing. Multi-criteria... more System investment decision has a very crucial role in any company aiming for efficient manufacturing. Multi-criteria decision making process is required to select the best among the alternatives. In this study, fuzzy AHP and fuzzy TOPSIS methods are used in a two-step methodology to select the suitable automated storage and retrieval system (AS/RS) so as to satisfy the expectations of the company. Eleven criteria are used in fuzzy AHP to calculate the criteria weights. These weights are then used in fuzzy TOPSIS to rank three AS/RS alternatives. The proposed model is used for selecting the right AS/RS in one of the leading consumer electronics company of Turkey.

An Adaptive Neuro-Fuzzy Inference System for Simulation of Pedestrians Behaviour at Unsignalized Roadway Crossings

by michele ottomanelli

Predikční mapa archeologických lokalit středního Pootaví. Mladší doba bronzová až časná doba laténská - Prediction map of archaeological sites in middle part of Otava river basin

by Jan John

John, J. - Chvojka, O. - Rytíř, L. 2003: Predikční mapa archeologických lokalit středního Pootaví. Mladší doba bronzová až časná doba laténská - Prediction map of archaeological sites in middle part of Otava river basin. In: E. Neustupný (Ed.), Příspěvky k prostorové archeologii 1, 72 - 91.

Multikriteriálne rozhodovanie pomocou fuzzy množín v prostredí GIS a jeho využitie v archeologickej predikcii (Multicriteria Decision Making Using Fuzzy Sets in GIS Environment and Its Application in the Archaeological Prediction)

by Tibor Lieskovský

Published in:Geodetický a kartografický obzor, ročník 57/99, 2011, číslo 8

Modelling of uncertainty in multicriteria decision making in prediction of archaeological sites in Slovakia.... more Modelling of uncertainty in multicriteria decision making in prediction of archaeological sites in Slovakia. Description of the
basic concept of fuzzy sets focusing on the possibility of its use in modelling uncertainty in spatial analysis. A few parameters
(slope, distance from watercourses, soil suitability, distance from fl uvial deposits, etc.) enter into the process of deciding
about appropriateness, or inadequacy of potential localities for the archaeological site. Representation of all the factors
implies a degree of uncertainty. To eliminate the impact of uncertain factors or inaccurate data are all parameters chosen by
appropriately modelled fuzzy sets. A practical solution of the spatial analysis using principles of fuzzy logic and fuzzy sets is
realized in the ArcGIS 10 software environment.

Bringing Flexibility to the Specification and Coordination of Temporal Dependencies among Multimedia Components

by Ivan Ricarte

Co-authored with André Coelho and Alberto Raposo. Published in SBMIDIA'2001.

We introduce a methodology for the high-level specification and decentralized coordination of temporal... more We introduce a methodology for the high-level specification and decentralized coordination of temporal interdependencies among multimedia document objects. Such methodology encompasses a three-step process comprising (i) the design of multimedia  presentation scenes by means of a fuzzy descriptive plan; (ii) the parsing of such layout to classify the multimedia entities that compose the scenes and to check the consistency of temporal relationships among them; and (iii) the generation of event-driven time and action managers as distributed mechanisms for the  orchestration of the elements presentation. This approach centers around a novel multimedia synchronization model based on fuzzy sets and software components concepts.

Using Fuzzy Petri Nets to Coordinate Collaborative Activities

by Ivan Ricarte

Co-authored with Alberto Raposo, André Coelho, and Léo Magalhães. Published in IFSA/NAFIPS World Congress, 2001.

This paper presents a fuzzy Petri net based approach suitable for the modeling of flexible coordination mechanisms to... more This paper presents a fuzzy Petri net based approach suitable for the modeling of flexible coordination mechanisms to deal with temporal interdependencies between collaborative tasks. Such approach is based on an extension of the Generalized Fuzzy Petri Net model, including the notion of time for the execution and synchronization of these tasks. A scenario of study is described, indicating the suitability of the proposal.

A Fuzzy Authoring Language for the High-level Specification of Component-based Multimedia Documents

by Ivan Ricarte

Co-authored with Andre LV Coelho. 2002.

In this paper, we present an authoring language for the high-level specification of temporal and spatial... more In this paper, we present an authoring language for the high-level specification of temporal and spatial interrelations between multimedia document objects. This work follows a synchronisation methodology based upon concepts of fuzzy sets and software components. As result, the designer is endowed with a more expressive and flexible modelling tool for creating multimedia scenarios, which is done by means of hierarchical fuzzy descriptive plans. As well, such approach gives support to the representation of inaccurate relationships and unpredictable situations. After discussing the semantics behind the language directives, an illustrative scenario is presented.

On the Fuzzy Spatio-temporal Specification of Multimedia Synchronisation Scenarios

by Ivan Ricarte

Co-authored with Andre L V Coelho. Published in Applications and science in soft computing, 2004

In this paper, we present an authoring language for the high-level specification of temporal and spatial... more In this paper, we present an authoring language for the high-level specification of temporal and spatial interrelations between multimedia document objects. This work follows a synchronisation methodology based upon concepts of fuzzy sets and software components. As result, the designer is endowed with a more expressive and flexible modelling tool for creating multimedia scenarios, which is done by means of hierarchical fuzzy descriptive plans. As well, such approach gives support to the representation of inaccurate relationships and unpredictable situations. After discussing the semantics behind the language directives, an illustrative scenario is presented.

Ontologia relacional fuzzy em sistemas de recuperação de informação

by Ivan Ricarte

Co-authored with Rachel Pereira and Fernando Gomide. Published in Encontro Nacional de Inteligência Artificial, 2005. In Portuguese.

Currently, document search in information retrieval systems is a
common task performed daily. The considerable... more Currently, document search in information retrieval systems is a
common task performed daily. The considerable growth of documents in databases increases the need of better information retrieval models and algorithms using n ew techniques of artificial intelligence. This paper presents an information retrieval model based on ontologies encoded by fuzzy relations. The model uses the principles of fuzzy set theory and approximate reasoning for knowledge representation and information search. Two query algorithms are suggested. Experimental results show that the fuzzy relational ontological model achieves better performance when compared with two alternative approaches based on thesauri and fuzzy conceptual network.

Fuzzy relational ontological model in information search systems

by Ivan Ricarte

Co-authored with Rachel Pereira and Fernando Gomide. Published in Capturing Intelligence, 2006

Ontology is an essential ingredient to improve information search efficiency and success. Ontology can be used to... more Ontology is an essential ingredient to improve information search efficiency and success. Ontology can be used to provide semantic-based access to the Web documents and extract meaningful information from texts. This chapter presents an information search model based on ontology encoded by fuzzy relations. The model uses the principles of fuzzy set theory and approximate reasoning for knowledge representation and information search. Two query algorithms are developed emphasizing, without loss of generality, document search. Experimental results show that the fuzzy relational ontological model performs better when compared with two alternative approaches based on thesauri and fuzzy conceptual network.

Using Multiple Related Ontologies in a Fuzzy Information Retrieval Model

by Ivan Ricarte

Co-authored with Angelica Leite. Published in WONTO'2008.

With the Semantic Web progress many independently developed distinct domain ontologies have to be shared and reused by... more With the Semantic Web progress many independently developed distinct domain ontologies have to be shared and reused by a variety of applications. The use of ontologies in information retrieval applications allows the retrieval of semantically related documents to an initial users’ query. This work presents a fuzzy information retrieval model for improving the document retrieval process considering a knowledge base composed of multiple domain ontologies that are fuzzy related. Each ontology can be represented independently as well as their relationships. This knowledge organization is used in a novel method to expand the user initial query and to index the documents in the collection. Experimental results show that the proposed model presents better overall performance when compared with another fuzzy-based approach for information retrieval.

A framework for information retrieval based on fuzzy relations and multiple ontologies

by Ivan Ricarte

Co-authored with Maria Angelica A Leite. Published in Advances in Artificial Intelligence – IBERAMIA, 2008

The use of knowledge in the information retrieval process allows the return of documents semantically related to the... more The use of knowledge in the information retrieval process allows the return of documents semantically related to the initial user’s query. This knowledge can be encoded in a knowledge base to be used in information retrieval systems. The framework for information retrieval based on fuzzy relations and multiple ontologies is a proposal to retrieve information using a knowledge base composed of multiple related ontologies whose relationships are expressed as fuzzy relations. Using this knowledge organization a new method to expand the user query is proposed. The framework provides a way that each ontology can be represented independently as well as their relationships. The proposed framework performance is compared with another fuzzy-based approach for information retrieval. Also the query expansion method is tested with the Apache Lucene search engine. In both cases the proposed framework improves the obtained results.

Fuzzy Information Retrieval Model Based on Multiple Related Ontologies

by Ivan Ricarte

Co-authored with Maria Angelica A Leite. Published in IEEE International Conference on Tools with Artificial Intelligence (ICTAI), 2008.

With the semantic web progress, encoding of knowledge bases as ontologies has increased. Information retrieval... more With the semantic web progress, encoding of knowledge bases as ontologies has increased. Information retrieval applications are employing this knowledge organization to enhance quality of results by returning documents semantically related and relevant to initial user's query. The proposed fuzzy information retrieval model retrieves information providing a framework to encode a knowledge base composed of multiple related ontologies whose relationships are expressed as fuzzy relations. This knowledge organization is used in a novel method to expand the user initial query and to index the documents in the collection. The model allows the ontologies, as well as the relationships among their concepts, to be represented independently. Experimental results show that the proposed model presents better overall performance when compared with another classical fuzzy-based approach for information retrieval.

Fuzzy Information Retrieval Model Based on Multiple Related Ontologies (Short paper)

by Ivan Ricarte

Co-authored with Angelica Leite. Published in EADCA'2009

With the World Wide Web popularity the information retrieval area has a new challenge intending to retrieve... more With the World Wide Web popularity the information retrieval area has a new challenge intending to retrieve information resources by their meaning by using a knowledge base. Nowadays ontologies are being used to model knowledge bases. To deal with knowledge subjectivity and uncertainty fuzzy set theory techniques are employed. Preceding works encode a knowledge base using just one ontology. But a document collection can deal
with different domain themes, expressed by distinct ontologies. In this work a way of knowledge organization and representation as multiple related ontologies was investigated and a method of query expansion was developed. The knowledge organization and the query expansion method were integrated in the fuzzy model for information retrieval based on mutiple related ontologies. The model performance was compared with another fuzzy-based approach for information retrieval and with the Apache Lucene search engine. In both cases the proposed model improves the
precision and recall measures.

Information retrieval with FROM: The fuzzy relational ontological model

by Ivan Ricarte

Co-authored with Rachel Pereira and Fernando Gomide. Published in International Journal of Intelligent Systems, 2009.

This paper presents FROM, the fuzzy relational ontological model, a novel approach to encode knowledge for information... more This paper presents FROM, the fuzzy relational ontological model, a novel approach to encode knowledge for information retrieval applications based upon a fuzzy set framework that consider more generic concepts differently from specific terms. Besides the model itself, the paper also presents a retrieval algorithm that exploits FROM features through the application of fuzzy operations that uses this knowledge to extend a user's query based on these fuzzy associations. Experimental results have shown that retrieval with FROM presented better overall performance than other fuzzy-based approaches for information retrieval.

Long-term prediction of discharges in Manwan Hydropower using adaptive-network-based fuzzy inference systems models

by K.W. Chau

Cheng, C.-T., Lin, J.-Y., Sun, Y.-G., Chau, K. Lecture Notes in Computer Science 3612 (PART III), pp. 1152-1161, 2005

Forecasting reservoir inflow is important to hydropower reservoir management and scheduling. An Adaptive-Network-based... more Forecasting reservoir inflow is important to hydropower reservoir management and scheduling. An Adaptive-Network-based Fuzzy Inference System (ANFIS) is successfully developed to forecast the long-term discharges in Manwan Hydropower. Using the long-term observations of discharges of monthly river flow discharges during 1953-2003, different types of membership functions and antecedent input flows associated with ANFIS model are tested. When compared to the ANN model, the ANFIS model has shown a significant forecast improvement. The training and validation results show that the ANFIS model is an effective algorithm to forecast the long-term discharges in Manwan Hydropower. The ANFIS model is finally employed in the advanced water resource project of Yunnan Power Group.

A Wide Input-Output Voltage Range AC-DC Converter with a Fuzzy PI+D Controller

by Farhad Ghadaki

"Co-authored with Mohammad Bagher Akbari Haghighat", "Co-authored with Mohammad-Ali Shamsi-Nejad"

This paper presents a two stage wide input-output voltage range ac-dc converter. First stage of the converter is a... more This paper presents a two stage wide input-output voltage range ac-dc converter. First stage of the converter is a commercially available front-end boost power factor corrector (PFC) and second stage is a simple step-down dc-dc converter. This work is based on classical off-line ac-dc power supplies architecture. The main improvement is the employment of Fuzzy Proportional-Integral-Derivative (FPI+D) controller to control the step-down converter. The main goal of the utilized controller is to regulate the output voltage in a wide range of reference voltage and load changes. Achieving these goals is possible by applying this robust controller that can handle inherent nonlinearities of dc-dc converters operating in both continuous-conduction-mode (CCM) and discontinuous-conduction-mode (DCM). Besides simulation results, a 200W universal-line hardware prototype was built to evaluate the proposed scheme experimentally. Developed prototype has the input voltage range of 85-265 Vac and the wide output voltage range between 10-200 Vdc.

Aplicación de la lógica difusa al análisis de viabilidad de una promoción inmobiliaria

by José Luis Ponz Tienda

2010
Msc. Thesis Doria Gil Senabre
tutores, Jose Luis Ponz Tienda, Maria Carmen Llinares Millan

Secondary Coordination at Closely‐Spaced Actuated Traffic Signals

by Lee D. Han

ASCE Journal of Transportation Engineering (2011) 137(11):751-759
with Xiaoli Sun and Tom Urbanik

This paper presents a method of addressing stochastic variation at closely spaced signalized intersections to provide... more This paper presents a method of addressing stochastic variation at closely spaced signalized intersections to provide secondary coordination to “minor” movements with significant traffic volumes. A neuro fuzzy signal control system was designed in this study to manage a non-coordinated movement to avoid queue spillback. Building on the conventional actuated-coordinated control system, the neuro-fuzzy controller does not lose the benefit of the primary coordination of the conventional controller but establishes a “secondary coordination” between the upstream coordinated phase (through phase) and the downstream non-coordinated phase (left-turn phase) on the basis of areal-time traffic demand. Under the neuro-fuzzy signal control, the traffic from the upstream intersection can arrive and join the queue at the downstream left-turn lane and be served in a timely fashion and thus reduce the likelihood of being delayed at the downstream intersection. The simulation results indicate that the neuro-fuzzy signal control consistently outperformed the conventional actuated-coordinated controller in terms of reduction in systemwide average delay and number of stops per vehicle under a wide range of traffic volumes by nearly 20% under heavier demand conditions.