International Journal of Computational Intelligence Systems

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1000 articles
J. Wesley Hines, Alexander Usynin
Pages: 94 - 102
CURRENT COMPUTATIONAL TRENDS IN EQUIPMENT PROGNOSTICS The article overviews current trends in research studies related to reliability prediction and prognostics. The trends are organized into three major types of prognostic models: failure data models, stressor models, and degradation models. Methods...
Z. Zenn Bien, Hyong-Euk Lee, Jun-Hyeong Do, Yong-Hwi Kim, Kwang-Hyun Park, Seung-Eun Yang
Pages: 77 - 93
The smart house under consideration is a service-integrated complex system to assist older persons and/or people with disabilities. The primary goal of the system is to achieve independent living by various robotic devices and systems. Such a system is treated as a human-in-the loop system in which...
Enrico Zio, Piero Baraldi, Irina Crenguta Popescu
Pages: 60 - 76
The applicability in practice of a diagnostic tool is strongly related to the physical transparency of the un- derlying models, for the interpretation of the relationships between the involved variables and for direct model inspection and validation. In this work, a methodology is developed for transforming...
Luis Martinez, Macarena Espinilla, Luis G. Perez
Pages: 148 - 158
Evaluation is a process that analyzes elements in order to achieve different objectives such as quality inspection, marketing and other fields in industrial companies. This paper focuses on sensory evaluation where the evaluated items are assessed by a panel of experts according to the knowledge...
Xian Shen, X.Z. Gao, Roufang Bie
Pages: 168 - 176
Artificial Immune Systems (AIS), which is inspired by the nature immune system, has been applied for solving complex computational problems in classification, pattern rec- ognition, and optimization. In this paper, the theory of the natural immune system is first briefly introduced. Next, we...
Valérie de Witte, Stefan Schulte, Etienne E. Kerre
Pages: 103 - 115
In this paper we present a new vector ordering ≤RGB for colours modelled in the RedGreenBlue colour model. The RedGreenBlue colour model becomes with this new ordering and associated minimum and maximum operators a complete lattice. We also have defined a complement co for colours in the RedGreenBlue...
Xiaobing Li, Da Ruan, Jun Liu, Yang Xu
Pages: 274 - 284
In selecting an optional alternative in an environment of multiple attribute group decision making, different attributes of the alternative are often considered as with quantitative and qualitative information. Consequently, decision making problems may include preference information in different formats....
Zuoliang Chen, Guoqing Chen
Pages: 262 - 272
Classification based on association rules is considered to be effective and advantageous in many cases. However, there is a so-called "sharp boundary" problem in association rules mining with quantitative attribute domains. This paper aims at proposing an associative classification approach, namely Classification...
Juan Carlos Augusto, Hui Wang, Jun Liu
Pages: 237 - 247
We present a framework for decision-making in relation to disaster management with a focus on situation assessment during disaster management monitoring. The use of causality reasoning based on the temporal evolution of a scenario provides a natural way to chain meaningful events and possible states...
Wensen An, Cecilio Angulo, Yanguang Sun
Pages: 299 - 303
Support vector machines (classification and regression) are powerful machine learning techniques for crisp data. In this paper, the problem is considered for interval data. Two methods to deal with the problem using support vector regression are proposed and two new methods for evaluating performance...
Gowrishankar, P.S. Satyanarayana
Pages: 379 - 389
In a wireless network environment accurate and timely estimation or prediction of network traffic has gained much importance in the recent past. The network applications use traffic prediction results to maintain its performance by adopting its behaviors. Network Service provider will use the prediction...
Juan Carlos Augusto, Jun Liu, Paul McCullagh, Hui Wang, Jian-Bo Yang
Pages: 361 - 378
The health system in developed countries is facing a problem of scalability in order to accommodate the increased proportion of the elderly population. Scarce resources cannot be sustained unless innovative technology is considered to provide health care in a more effective way. The Smart Home provides...
Nicolas Castin, Lorenzo Malerba, Roberto Pinheiro Domingos
Pages: 340 - 352
procedures for the calculation of point-defect migration energies in Atomistic Kinetic Monte Carlo (AKMC) simulations, as functions of the Local Atomic Configuration (LAC). Two approaches are considered: the Cluster Expansion (CE) and the Artificial Neural Network (ANN). The first is found to be unpromising...
Ashfaqur Rahman, Abdus Salam, Mahfuzul Islam, Partha Sarker
Pages: 304 - 312
Computing object distance using image processing is an important research area in the field of computer vision and robot navigation applications. In this paper we have proposed a new method to compute the distance of an object using a single image. According to our observation there exists a relationship...
Shuchita Upadhyaya, Alka Arora, Rajni Jain
Pages: 10 - 16
Clustering algorithms give general description of clusters, listing number of clusters and member entities in those clusters. However, these algorithms lack in generating cluster description in the form of pattern. From data mining perspective, pattern learning from clusters is as important as cluster...
J.A. Antonino-Daviu, M. Riera-Guasp, M. Pineda-Sanchez, J. Pons-Llinares, R. Puche-Panadero, J. Perez-Cruz
Pages: 158 - 167
Recognition of characteristic patterns is proposed in this paper in order to diagnose the presence of electromechanical faults in induction electrical machines. Two common faults are considered; broken rotor bars and mixed eccentricities. The presence of these faults leads to the appearance of frequency...
Abdelhamid Bouchachia
Pages: 147 - 157
This paper introduces a novel ensemble learning approach based on recurrent radial basis function networks (RRBFN) for time series prediction with the aim of increasing the prediction accuracy. Standing for the base learner in this ensemble, the adaptive recurrent network proposed is based on the...
Marcus Vinicius Carvalho da Silva, Nadia Nedjah, Luiza de Macedo Mourelle
Pages: 115 - 123
Network-on-chip (NoC) are considered the next generation of communication infrastructure, which will be omnipresent in most of industry, office and personal electronic systems. In platform-based methodology, an application is implemented by a set of collaborating intellectual properties (IPs) blocks....