Journal of Intelligent & Fuzzy Systems - Volume 28, issue 5

Authors: Li, Yingjie | Wang, Ran | Shiu, Simon C.K.

Article Type: Research Article

Abstract: Choosing representative samples and removing data redundancy are two key issues in large-scale data classification. This paper proposes a new model, named interval extreme learning machine (ELM), for big data classification with continuous-valued attributes. The interval ELM model is built up based on two techniques, i.e., discretization of conditional attributes and fuzzification of class labels. First, inspired by the traditional decision tree (DT) induction algorithm, each conditional attribute is discretized into a number of intervals based on uncertainty reduction scheme. Then, the center and range of each interval are calculated as the mean and standard deviation of the values in …it. Afterwards, the samples in the same intervals with regard to all the conditional attributes are merged as one record, and a fuzzification process is performed on the class labels. As a result, the original data set is transferred into a smaller one with fuzzy classes, and the interval ELM model is developed. Experimental comparisons demonstrate the feasibility and effectiveness of the proposed approach. Show more

Keywords: Extreme learning machine, interval, uncertainty reduction, big data

DOI: 10.3233/IFS-141520

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 5, pp. 2391-2403, 2015

Authors: Fuentes-Fernández, Rubén | Balsa, João

Article Type: Research Article

Abstract: Ambient Intelligence (AmI) systems are collections of interconnected services that use heterogeneous devices to integrate smoothly in the everyday environment of their users. Engineering these systems is a challenging task, where designers need to deal with issues such as information management, users’ profiles and activities, privacy, distribution, or continuous availability. The application of the multi-agent paradigm to develop these systems has been one of the most active lines of research in the area. Its abstractions of intentional and social agents are useful to analyze AmI systems with an integrated view of people and the services working for them. Moreover, this …paradigm already offers solutions to deal with many of the key aspects of AmI. This special issue highlights some state-of-the-art works in this line. It presents contributions regarding agent-oriented architectures and development processes for AmI, as well as illustrative industrial systems built under this approach. Show more

Keywords: Ambient Intelligence, agent, multi-agent system, architecture, development process

DOI: 10.3233/IFS-151618

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 5, pp. 2405-2407, 2015