Hybrid expert systems: A survey of current approaches and applications

Şahin, Seda; Tolun, Mehmet R.; Hassanpour, Reza

doi:10.1016/j.eswa.2011.08.130

Cited by 125 publications

(64 citation statements)

References 68 publications

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“…Desde su surgimiento hasta la fecha, los sistemas expertos han proliferado en muchos campos del actuar humano; una muestra de esa afirmación son los análisis hechos por Liao [2] y Sahin [3]. El primero se enfoca en los sistemas desarrollados entre 1995 y el 2004, mientras el segundo muestra una panorámica que abarca el periodo entre 1998 y el 2010, y se centra en los sistemas expertos híbri-dos.…”

Section: Introductionunclassified

Sistema experto para la identificación de plásticos

Brito

Rodríguez

2016

ing. Solidar

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Introducción: este artículo de investigación presenta una actualización del proyecto “Sistema Experto para la selección de materiales plásticos para el diseño y la elaboración de nuevos productos” desarrollada durante 1990 en la Universidad Central “Marta Abreu” de Las Villas. El objetivo de la investigación actual, realizada durante el 2015 en la Universidad Cooperativa de Colombia, es actualizar el sistema experto desarrollado en 1990. Metodología: para el desarrollo del sistema experto, se usó la metodología Common kads, la cual permite estructurar el conocimiento al hacer una distinción entre el dominio de la aplicación, la tarea y la inferencia, lo que facilita la reutilización de componentes. En el proceso de inferencia, se usa la dirección de búsqueda dirigida por objetivos, debido a las características del conocimiento contenido en las bases, en las cuales el proceso de inferencia comienza sin la existencia de datos preliminares. Resultados: la nueva versión del sistema mejora las inferencias, ofrece una interfaz más amigable y amplía el conocimiento. Conclusiones: la ampliación de las bases de conocimiento, adaptadas a nuevas situaciones, incide en la obtención de respuestas más fundamentadas y mejores; la implementación del nuevo sistema sobre ucShell, versión 3.0 proporciona una mejoría notable en la interfaz, que incluye la posibilidad de ofrecer imágenes y videos durante el proceso de inferencia y admite bases de conocimientos de cualquier tamaño y la facilidad de cambiarse entre ellas.

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Section: Introductionunclassified

Sistema experto para la identificación de plásticos

Brito

Rodríguez

2016

ing. Solidar

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“…Fuzzy sets and systems are attributed as an excellent method to deal with situations where the element of uncertainty and imprecision is high, typically prevalent in complex environments (see Wagner and Hagras, 2010). A number of surveys (Tsang, 2009;Krollner et al, 2010;Sahin et al, 2012) place Artificial Neural Networks (ANNs) amongst the most popular learning techniques in AI-based financial applications and hybrid models. ANNs, especially in conjunction with fuzzy logic, were found to provide better forecasts.…”

Section: A C C E P T E D Mmentioning

confidence: 99%

Improving risk-adjusted performance in high frequency trading using interval type-2 fuzzy logic

Vella

2016

Expert Systems with Applications

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Highlights• We investigate the viability of Type-2 fuzzy systems in high frequency trading.• We propose Type-2 models based on a generalisation of the popular ANFIS model.• Type-2 models score significant risk adjusted performance improvements over Type-1.• Benefits of Type-2 models increase with higher trading frequencies. AbstractIn this paper, we investigate the ability of higher order fuzzy systems to handle increased uncertainty, mostly induced by the market microstructure noise inherent in a high frequency trading (HFT) scenario. Whilst many former studies comparing type-1 and type-2 Fuzzy Logic Systems (FLSs) focus on error reduction or market direction accuracy, our interest is predominantly risk-adjusted performance and more in line with both trading practitioners and upcoming regulatory regimes. We propose an innovative approach to design an interval type-2 model which is based on a generalisation of the popular type-1 ANFIS model. The significance of this work stems from the contributions as a result of introducing type-2 fuzzy sets in intelligent trading algorithms, with the objective to improve the risk-adjusted performance with minimal increase in the design and computational complexity. Overall, the proposed ANFIS/T2 model scores significant performance improvements when compared to both standard ANFIS and Buy-and-Hold methods. As a further step, we identify a relationship between the increased trading performance benefits of the proposed type-2 model and higher levels of microstructure noise. The results resolve a desirable need for practitioners, researchers and regulators in the design of expert and intelligent systems for better management of risk in the field of HFT.

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“…An ES is a computer program that reasons and uses a knowledge base to solve complex problems in a particular domain (Krishnamoorthy & Rajeev, 1996;Kusiak, 1990). Sahin et al (2012) show a statistical analysis of hybrid ES approaches and their applications. The publications have an increasing trending as an indicator of the popularity of hybrid ES.…”

Section: Background and Literature Reviewmentioning

confidence: 99%

A hybrid expert system, clustering and ant colony optimization approach for scheduling and routing problem in courier services

López-Santana¹,

Rodríguez-Vásquez²,

Méndez-Giraldo³

2018

10.5267/j.ijiec

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This paper focuses on the problem of scheduling and routing workers in a courier service to deliver packages for a set of geographically distributed customers and, on a specific date and time window. The crew of workers has a limited capacity and a time window that represents their labor length. The problem deals with a combination of multiples variants of the vehicle routing problem as capacity, multiple periods, time windows, due dates and distance as constraints. Since in the courier services the demands could be of hundreds or thousands of packages to be delivered, the problem is computationally unmanageable. We present a threephase solution approach. In the first phase, a scheduling model determines the visit date for each customer in the planning horizon by considering the release date, due date to visit and travel times. We use an expert system based on the know-how of the courier service, which uses an inference engine that works as a rule interpreter. In the second phase, a clustering model assigns, for each period, customers to workers according to the travel times, maximum load capacity and customer's time windows. We use a centroid based and sweep algorithms to solve the resulted problem. Finally, in the third phase, a routing model finds the order in which each worker will visit all customers taking into account their time windows and worker's available time. To solve the routing problem we use an Ant Colony Optimization metaheuristic. We present some numerical results using a case study, in which the proposed method of this paper finds better results in comparison with the current method used in the case study.

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Hybrid expert systems: A survey of current approaches and applications

Cited by 125 publications

References 68 publications

Sistema experto para la identificación de plásticos

Sistema experto para la identificación de plásticos

Improving risk-adjusted performance in high frequency trading using interval type-2 fuzzy logic

A hybrid expert system, clustering and ant colony optimization approach for scheduling and routing problem in courier services

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