Journal of Intelligent & Fuzzy Systems - Volume 22, issue 2-3

Authors: Kim, Kyung-Joong | Cho, Sung-Bae

Article Type: Other

DOI: 10.3233/IFS-2011-0475

Citation: Journal of Intelligent & Fuzzy Systems, vol. 22, no. 2-3, pp. 53-55, 2011

Authors: Tan, Shing Chiang | Lim, Chee Peng

Article Type: Research Article

Abstract: In this paper, an Evolutionary Artificial Neural Network (EANN) that combines the Fuzzy ARTMAP (FAM) network and a Hybrid Evolutionary Programming (HEP) model is introduced. The proposed FAM-HEP model, which combines the strengths of FAM and HEP, is able to construct its network structure autonomously as well as to perform learning and evolutionary search and adaptation concurrently. The effectiveness of the proposed FAM-HEP network is assessed empirically using several benchmark data sets and a real medical diagnosis problem. The performance of FAM-HEP is analyzed, and the results are compared with those of FAM-EP, FAM, and other classification models. In general, …the results of FAM-HEP are better than those of FAM-EP and FAM, and are comparable with those from other classification models. The study also reveals the potential of FAM-HEP as an innovative EANN model for undertaking pattern classification problems in general, and a promising computerized decision support tool for tackling medical diagnosis tasks in particular. Show more

Keywords: Fuzzy ARTMAP, hybrid evolutionary programming, pattern classification, medical diagnosis

DOI: 10.3233/IFS-2011-0476

Citation: Journal of Intelligent & Fuzzy Systems, vol. 22, no. 2-3, pp. 57-68, 2011

Authors: Maia, José Everardo B. | Barreto, Guilherme A. | Coelho, André L.V.

Article Type: Research Article

Abstract: In this paper, a recently proposed evolutionary self-organizing map is extended and applied to visual tracking of objects in video sequences. The proposed approach uses a simple geometric template to track an object executing a smooth movement represented by affine transformations. The template is selected manually in the first frame and consists of a small number of keypoints and the neighborhood relations among them. The coordinates of the keypoints are used as the coordinates of the nodes of a non-regular grid defining a self-organizing map that represents the object. The weight vectors of each node in the output grid are …updated by an evolutionary algorithm and used to locate the object frame by frame. Qualitative and quantitative evaluations indicate that the proposed approach present better results than those obtained by a direct method approach. Additionally, the proposed approach is evaluated under situations of partial occlusion and self-occlusion, and outliers, also presenting good results. Show more

DOI: 10.3233/IFS-2011-0477

Citation: Journal of Intelligent & Fuzzy Systems, vol. 22, no. 2-3, pp. 69-81, 2011

Authors: Kim, Kyung-Joong | Park, Jung Guk | Cho, Sung-Bae

Article Type: Research Article

Abstract: In a genetic algorithm, the search process maintains multiple solutions and their interactions are important to accelerate the evolution. If the pool of solutions is dominated by the single fittest individual in the early generation, there is a risk of premature convergence losing exploration capability. It is necessary to consider not only the fitness of solutions but also the similarity to other individuals. This speciation idea is beneficial to several application domains with evolutionary computation but it requires objective distance measures to calculate the similarity of individuals. It raises a challenging research issue to measure the distance between two evolutionary …neural networks (ENN). In this paper, we surveyed several distance measures proposed for ENN and compared their performance for pattern classification problems with two different genetic representations (matrix-based and topology growing (NEAT) approaches). Although there was no dominant distance measure for the pattern classification problems, it showed that the behavioral distance measures outperformed the architectural one for matrix-based representation and. For NEAT, NeuroEdit showed better accuracy against compatibility distance measure. Show more

Keywords: Speciation, premature convergence, distance measures, evolutionary neural networks, pattern classification, NEAT

DOI: 10.3233/IFS-2011-0478

Citation: Journal of Intelligent & Fuzzy Systems, vol. 22, no. 2-3, pp. 83-92, 2011

Authors: Mańdziuk, Jacek | Jaruszewicz, Marcin

Article Type: Research Article

Abstract: This goal of the paper is introduction and experimental evaluation of neuro-genetic system for short-term stock index prediction. The system works according to the following scheme: first, a pool of input variables are defined through technical data analysis. Then GA is applied to find an optimal set of input variables for a one day prediction. Due to the high volatility of mutual relations between input variables, a particular set of inputs found by the GA is valid only for a short period of time and a new set of inputs is calculated every 5 trading days. The data is gathered …from the German Stock Exchange (being the target market) and two other markets (Tokyo Stock Exchange and New York Stock Exchange) together with EUR/USD and USD/JPY exchange rates. The method of selecting input variables works efficiently. Variables which are no longer useful are exchanged with the new ones. On the other hand some, particularly useful, variables are consequently utilized by the GA in subsequent independent prediction periods. The proposed system works well in cases of both upward or downward trends. The effectiveness of the system is compared with the results of four other models of stock market trading. Show more

Keywords: Financial forecasting, stock index prediction, neuro-genetic system, neural networks, genetic algorithms, time series analysis, trend prediction, technical analysis, oscillators, pattern extraction

DOI: 10.3233/IFS-2011-0479

Citation: Journal of Intelligent & Fuzzy Systems, vol. 22, no. 2-3, pp. 93-123, 2011

Authors: Duro, Richard J. | Bellas, Francisco | Prieto, Abraham | Paz-López, Alejandro

Article Type: Research Article

Abstract: This paper discusses an algorithm that provides a way to obtain ensembles of collaborating artificial neural networks (ANNs) online. That is, its purpose is to find solutions to problems based on the interaction of sets of, in principle, heterogeneous ANNs whose joint behaviour results in an emergent solution. This approach is intrinsically able to handle lifelong adaptation within the society in order to comply with changing situations or demands in dynamic environments. It is called Asynchronous Situated Coevolution (ASiCo) and was designed for the lifelong coevolution of artificial neural network societies. ASiCo deals with the evolutionary part of neuroevolution and …it can support any type of neural network structure or even neural network construction mechanism. Consequently, it can be extended with some of the techniques found in single ANN neuroevolutionary mechanisms when considering the simultaneous evolution of network weights and network topology. The operation and characteristics of this strategy are illustrated through some experiments carried out using a well known benchmark collaboration task. Show more

DOI: 10.3233/IFS-2011-0480

Citation: Journal of Intelligent & Fuzzy Systems, vol. 22, no. 2-3, pp. 125-139, 2011

Authors: Oliver, Jose Luis | Tortosa, Leandro | Vicent, Jose F.

Article Type: Research Article

Abstract: A 2D triangle mesh simplification model is described in this paper, with the main objective of preserving the shape of the original mesh. The proposed model consists of a self-organizing algorithm whose objective is to generate the positions of the nodes of the simplified mesh; afterwards, a triangulation algorithm is performed to reconstruct the triangles of the new simplified mesh. The self-organizing algorithm is an unsupervised learning algorithm that provides a set of nodes representing the best approximation of the original mesh. An adaptation of the neural network algorithm is proposed with the primary objective to work in the context …of urban transport networks. We verify the effectiveness of this model through the design and development of some urban network problems. Specifically, the algorithm is applied to two real problems, the first one is the design of a tramway network in a town, and the second one is the design of an information point network within a real bus transport network. Show more

DOI: 10.3233/IFS-2011-0481

Citation: Journal of Intelligent & Fuzzy Systems, vol. 22, no. 2-3, pp. 141-154, 2011