In this article the design and development of a hierarchical fuzzy logic system is investigated. A new method using an evolutionary algorithm for design of hierarchical fuzzy logic system for prediction and modelling of interest rates in Australia is developed. The hierarchical system is developed to model and predict three months (quarterly) interest rate fluctuations. This research study is u...

The development of the internet has been triggering numerous mutations in the visualization of actors in economic network independence distribution (ENID) of goods. ENID overcomes the physical barriers of shop-floor space so unprecedented variety of products could be offered to the customers. Avoidance of expensive trade space allows suppliers to reduce price compared to those in the physical w...

This article presents a neural network model that permits to build a conceptual hierarchy to approximate functions over a given interval. Bio-inspired axo-axonic connections are used. In these connections the signal weight between two neurons is computed by the output of other neuron. Such arquitecture can generate polynomial expressions with lineal activation functions. This network can approx...

Image location prediction is to estimate the geolocation where an image is taken. Social image contains heterogeneous contents, which makes image location prediction nontrivial. Moreover, it is observed that image content patterns and location preferences correlate hierarchically. Traditional image location prediction methods mainly adopt a single-level architecture, which is not directly adapt...

We present a novel formalism for introducing deep belief features to Hierarchical Machine Translation Model. The deep features are generated by unsupervised training of a deep belief network built with stacked sets of Restricted Boltzmann Machines. We show that our new deep feature based hierarchical model is better than the baseline hierarchical model with gains for two different languages pai...

Object recognition and categorization is a fundamental aspect of cognition in humans and animals. Models have been implemented around the idea that categories are sets of frequently co-occurring features. Out of these models a question has been raised, namely what is the mechanism by which we learn a hierarchically organized set of categories, including types and subtypes? In this paper we intr...