International Journal of Computational Intelligence Systems

This paper addresses the issue of non-uniform motion deblurring for a single photograph. The main difficulty of spatially variant motion deblurring is that, the deconvolution algorithm can not directly be used to estimate blur kernel, due to the kernel of different pixels are different with each other....

This paper presents a new feature selection framework based on the -norm, in which data are summarized by their moments of the class conditional densities. However, discontinuity of the -norm makes it difficult to find the optimal solution. We apply a proper approximation of the -norm and a bound on...

Mining frequent itemsets over transaction data streams is critical for many applications, such as wireless sensor networks, analysis of retail market data, and stock market predication. The sliding window method is an important way of mining frequent itemsets over data streams. The speed of the sliding...

Industries are now moving towards PC-based control from PLC (Programmable Logic Control) based control as the PC (personal computer) is easily available and capable of implementing various control strategies to improve productivity. Advances in both hardware and software technology are expediting this...

In this work, an implicit Lagrangian for the dual twin support vector regression is proposed. Our formulation leads to determining non-parallel –insensitive down- and up- bound functions for the unknown regressor by constructing two unconstrained quadratic programming problems of smaller size,...

Triangular intuitionistic fuzzy numbers (TIFNs) are a special kind of intuitionistic fuzzy sets (IFSs) on a real number set. TIFNs are useful to deal with ill-known quantities in decision data and decision making problems themselves. The purpose of this paper is on developing a new ranking method of...

Content-based recommender systems (CBRS) are tools that help users to choose items when they face a huge amount of options, recommending items that better fit the user's profile. In such a process, it is very interesting to know which features of the items are more important for each user, thus the CBRS...

As the electrical industry restructures many of the traditional algorithms for controlling generating units, they need either modification or replacement. In the past, utilities had to produce power to satisfy their customers with the objective to minimize costs and actual demand/reserve were met. But...

Clustering for data aggregation is essential nowadays for increasing the wireless sensor network (WSN) lifetime, by collecting the monitored information within a cluster at a cluster head. The clustering algorithm reduces overall transmission of data from each sensor to the sink node thus energy spent...

Process capability indices (PCIs) provide numerical measures on whether a process confirms to the defined capability prerequisite. They have been used to measure the ability of process to decide how well the process meets the specification limits (SLs). The PCIs have been successfully applied by companies...

This paper considers the problem of non-fragile finite-time guaranteed cost fuzzy control for continuous-time nonlinear systems. Firstly, the definition on finite-time stability (FTS) for continuous-time nonlinear systems is provided and we give a novel and explicit interpretation for non-fragile finite-time...

As a knowledge representation tool, ontologies have been widely applied in many fields such as knowledge management and information integration, etc. Ontology measurement is an important challenge in the field of knowledge management in order to manage the development of ontology based systems and reduce...

A novel algorithm of audio aggregation watermarking was proposed in this paper for copyright protection. The algorithm not only protects copyright of a single audio in audio aggregation but also protects copyright of the whole audio aggregation. The experimental results showed the watermark of aggregate...

This paper is focused on α-generalized semantic resolution automated reasoning method in linguistic truth-valued lattice-valued propositional logic. Concretely, α-generalized semantic resolution for lattice-valued propositional logic ()P(X) is equivalently transformed into that for lattice-valued...

The purpose of this study is to introduce a new regression model, based on the least squares method, when the available data of both explanatory variable(s) and response variable are interval-valued fuzzy (IVF) numbers. The proposed method is based on a new metric on the space of IVF numbers, which is...

Interval set theory and soft set theory are mathematical tools for dealing with uncertainty information. As a combination of interval set and soft set, recently, we introduced the new notion of interval soft sets. In this paper we further research interval soft sets and its application. We investigate...