Journal of Intelligent & Fuzzy Systems - Volume 21, issue 1, 2

Authors: Lovrek, I. | Howlett, R.J. | Lim, C.-P. | Jain, L.C. | Phillips-Wren, G.

Article Type: Correction

DOI: 10.3233/IFS-2010-0430

Citation: Journal of Intelligent & Fuzzy Systems, vol. 21, no. 1, 2, pp. 1-3, 2010

Authors: Chang, J. | Chowdhury, N.K. | Lee, H.

Article Type: Research Article

Abstract: Recently, travel time prediction has become a crucial part of trip panning and dynamic route guidance for many advanced traveler information and transportation management systems. Moreover, a scalable prediction system with high accuracy is critical for the successful deployment of ATIS (Advanced Travelers Information Systems) in road networks. In this paper, we propose two travel time prediction algorithms using naïve Bayesian classification and rule-based classification. Both classification techniques provide a velocity class to be used for measuring travel time accurately. Our algorithms exhibit high accuracy in predicting travel time when using a large amount of historical traffic database. In addition, …our travel time prediction algorithms are suitable for road networks with arbitrary travel routes. It is shown from our performance comparison, our travel time prediction algorithms significantly outperform the existing prediction algorithms, such as the link-based algorithm, the switching model, and the linear regression algorithm. In addition, it is revealed that our algorithm using naïve Bayesian classification is better on the performance of mean absolute relative error than our algorithm using rule-based classification. Show more

Keywords: Travel time prediction, Intelligent transportation systems, ATIS (Advanced Travelers Information Systems), Naïve Bayesian classification, Rule-based classification

DOI: 10.3233/IFS-2010-0431

Citation: Journal of Intelligent & Fuzzy Systems, vol. 21, no. 1, 2, pp. 5-7, 2010

Authors: Németh, E. | Hangos, K.M. | Lakner, R.

Article Type: Research Article

Abstract: An ontology for representing operating, safety and control procedures is proposed in this paper that descibes the procedure steps and their connections, and enables to represent exceptions during the normal flow of execution in terms of time-out and failed conditions. The procedure ontology is defined within interconnected components of the process plant and the diagnostic analysis based on risk assessment information, and has been implemented as an integrated ontology in a diagnostic framework using the the Protégé ontology editor. A novel diagnostic method based on following these procedures and combining observed malfunctions with Failure Mode and Effects Analysis (FMEA) information …is also proposed. The proposed ontology and the diagnostic method are illustrated on a simple operating procedure. Show more

Keywords: Knowledge management, intelligent systems, ontology, multi-agent systems

DOI: 10.3233/IFS-2010-0432

Citation: Journal of Intelligent & Fuzzy Systems, vol. 21, no. 1, 2, pp. 19-31, 2010

Authors: Mastrogiovanni, F. | Sgorbissa, A. | Zaccaria, R.

Article Type: Research Article

Abstract: In Ambient Intelligence (AmI) scenarios, such as smart homes and similar assistive environments, system designers, medical personnel and – in general – non technically skilled people need to specify what to monitor with respect to occurrences of events and human activities. A Situation Description Language, called SDL, is introduced that allows to specify activity recognition templates as simple programs made up of formulas, and is provided with suitable tools to translate programs into symbolic structures maintained within an Ontology. Once encoded, formulas originate classification procedures that operate on actual sensory data. The focus of this paper is on formal specification …of SDL formulas and corresponding translation within the Ontology. Examples are reported that demonstrate the benefits on context modeling introduced by the adoption of SDL. Show more

Keywords: Context-aware systems, activity recognition, knowledge representation, ontologies

DOI: 10.3233/IFS-2010-0433

Citation: Journal of Intelligent & Fuzzy Systems, vol. 21, no. 1, 2, pp. 33-48, 2010

Authors: Yoshimura, E. | Tsuchiya, S. | Watabe, H. | Kawaoka, T.

Article Type: Research Article

Abstract: This paper proposes one of a response production method on chatting system automatically. Our approach is applied to Japanese language. This is not necessary that it achieve a task. The responses support our conversation flow and let us produce a new topic. The system will get much information for the speaker by performing much conversation with this system. Based on the much information by a conversation with the system, the flexible reply for a speaker will come to be possible. In the present paper, we propose a response by association of the input sentence. For example, we associate “medical treatment” …with “hospital”. We reply then using the association word. If, like humans, a machine can reply using the association word, it will return various flexible responses. Show more

Keywords: Association response, natural conversation, commonsense

DOI: 10.3233/IFS-2010-0434

Citation: Journal of Intelligent & Fuzzy Systems, vol. 21, no. 1, 2, pp. 49-55, 2010

Authors: Pérez-Ortega, J. | Pazos, R.A. | Ruiz-Vanoye, J.A. | Frausto-Solís, J. | González-Barbosa, J.J. | Fraire-Huacuja, H.J. | Díaz-Parra, O.

Article Type: Research Article

Abstract: The only metric that had existed so far to determine the best algorithm for solving an general Asymmetric Traveling Salesman Problem (ATSP) instance is based on the number of cities; nevertheless, it is not sufficiently adequate for discriminating the best algorithm for solving an ATSP instance, thus the necessity for devising a new metric through the use of data-mining techniques. In this paper we propose: (1) the use of a genetic distance metric for improving the selection of the algorithms that best solve a given instance of the ATSP and (2) the use of discriminant analysis as a means for …predictive learning (data-mining techniques) aiming at selecting meta-heuristic algorithms. Show more

Keywords: Inductive learning, discriminant analysis, data-mining techniques, machine learning, genetic distance metric

DOI: 10.3233/IFS-2010-0435

Citation: Journal of Intelligent & Fuzzy Systems, vol. 21, no. 1, 2, pp. 57-64, 2010

Authors: Yap, Keem Siah | Lim, Chee Peng | Mohamad-Saleh, Junita

Article Type: Research Article

Abstract: Generalized Adaptive Resonance Theory (GART) is a neural network model based on the integration of Gaussian ARTMAP and the Generalized Regression Neural Network. As demonstrated in our previous work, GART is capable of online learning and is effective in tackling both classification and regression tasks. In this paper, we propose an Enhanced GART (EGART) network whereby the capability of GART is further enhanced with the Laplacian function, a new vigilance function, a new match-tracking mechanism, and a fuzzy rule extraction procedure. The applicability of EGART to pattern classification and fuzzy rule extraction problems is evaluated using three benchmark medical data …sets and one real medical diagnosis problem. The experimental results are analyzed, discussed, and compared with other reported results. The outcomes demonstrate that EGART is capable of producing high accuracy rates and of extracting useful rules for tackling medical pattern classification problems. Show more

Keywords: Adaptive resonance theory, generalized regression neural network, fuzzy rule extraction, pattern classification, medical diagnosis

DOI: 10.3233/IFS-2010-0436

Citation: Journal of Intelligent & Fuzzy Systems, vol. 21, no. 1, 2, pp. 65-78, 2010

Authors: Balas, V.E. | Jain, L.C.

Article Type: Research Article

Abstract: A necessary strategy to improve our technologies is to provide them with useful pieces of deterministic previous knowledge about the processes and the equipment. Our attention was previously focused on the industrial control systems, implemented with low level devices (controllers, sensors, actuators), that need knowledge on the specific controlled plants as well as on the general theoretical foundations. This was done on-line with the help of internal models, or off-line with planners whose design is assisted by simulations. This paper is orienting the same effort in the direction of the intelligent sensors field. A brief overview of the relationship between …sensors and knowledge is provided. A particular architecture of sensors relying on modeling techniques and some internal model estimators for the velocity and for the weariness of the railway cars are illustrating the role of the models in sensors and estimators. Show more

Keywords: Internal model, sensor fusion, fuzzy-interpolative system

DOI: 10.3233/IFS-2010-0437

Citation: Journal of Intelligent & Fuzzy Systems, vol. 21, no. 1, 2, pp. 79-88, 2010

Authors: Tran, M.D.J. | Lim, C.P. | Abeynayake, C. | Jain, L.C.

Article Type: Research Article

Abstract: In this paper, the Fuzzy ARTMAP (FAM) neural network is used to classify metal detector signals into different categories for automated target discrimination. Feature extraction of the metal detector signals is conducted using a wavelet transform technique. The FAM neural network is then employed to classify the extracted features into different target groups. A series of experiments using individual FAM networks and a voting FAM network is conducted. Promising classification accuracy rates are obtained from using individual and voting FAM networks, respectively. The experimental outcomes positively demonstrate the effectiveness of the generated features, and of the FAM network in classifying …metal detector signals for automated target discrimination tasks. Show more

Keywords: Metal detector, wavelet transform, fuzzy ARTMAP neural network, majority voting, automated target discrimination

DOI: 10.3233/IFS-2010-0438

Citation: Journal of Intelligent & Fuzzy Systems, vol. 21, no. 1, 2, pp. 89-99, 2010

Authors: Franklin, S. | Finn, A. | Pattison, J. | Jain, L.C.

Article Type: Research Article

Abstract: Scene understanding is an essential element for the exploration of unknown territory using mobile robots. In this regard, scene understanding refers to the identification and localization of elements within the scene. When the scene is dynamic or has objects that move around, they need to be characterized and discriminated from the static elements, which are essential for SLAM (Simultaneous Localization And Mapping) when external or global localization information is not available. We present techniques and algorithms to accomplish these goals with regard to a scenario where we have a co-operative of robots having three degrees of freedom (x, y, θ) …and equipped with a fixed monocular camera, observing a dynamic scene. The strategy is to localize the static elements of the scene and then estimate the velocity and trajectory of moving objects. The latter is much more difficult to solve than the former. We also present co-ordination and steering strategies for reducing the errors associated with the estimated parameters. Show more

Keywords: Computational intelligence, approximate reasoning, compositional rule of inference, operation risk, symptom levels, parametric membership functions

DOI: 10.3233/IFS-2010-0439

Citation: Journal of Intelligent & Fuzzy Systems, vol. 21, no. 1, 2, pp. 101-112, 2010