This paper describes a novel connectionist system for dialogue processing. Based on a script-like formalism, the system consists of several modular neural networks which can track the semantic flow of a dialogue. The system can be extended to understand and translate dialogues in a fixed domain. This research was partially supported by ATR Interpreting Telephony Research Laboratories, NEC and S...

Lithium-ion batteries are commonly used in electric vehicles, mobile phones, and laptops. These demonstrate several advantages, such as environmental friendliness, high energy density, long life. However, battery overcharging overdischarging may occur if the not monitored continuously. Overcharging causes fire explosion casualties, a reduction capacity In addition, internal resistance of varies...

organising robot action control system using language for instruction. examine a modular neural network approach for the control of a robot to perform litter. both modular and traditional instructions were equally effective in facilitating The other result revealed that the use of modular approach utilizing decision tree. Abstract. Montgomery modular multiplication constitutes the “arithto our ...

Medium Neural Networks (MNN), Whale Optimization Algorithm (WAO), and Support Vector Machine (SVM) methods are frequently used in the literature for estimating electricity demand. The objective of this study was to make an estimation demand Turkey’s mainland with use mixed MNN, WAO, SVM. Imports, exports, gross domestic product (GDP), population data based on input from 1980 2019 Turkey, demand...

In this paper, the behavior of Modular and Non-Modular Neural Networks trained with the classical backpropagation algorithm in batch mode and applied to classification problems with Multi-Class imbalance is studied. Three different cost functions are introduced in the training algorithm in order to solve the problem in four different databases. The proposed strategies show an improvement in the...

A relevant research field is the development of closed-loop combinations of neural tissue and robotics, such as animats and hybrots [4]. As such, a proposed framework for a simple, modular synthetic organism will be evaluated. A closed-loop circulatory system would be used to sustain a “brain” via homeostatic maintenance of a balance of essential nutrients and waste removal. The modular “brains...

An approach to solving the problem of machining time estimation in production of complex products within CNC machining systems is presented in the paper. Heuristic analysis of the process is used to define the attributes of influence to machining time. For the problem of estimating machining time the following „Neural Computing techniques“ are used: Back-Propagation Neural Network, Modular Neur...

Built from a need for modelling cognitive processes, a modular neural network is designed as the “brain” of a virtual robot moving in a prey-predator environment. The robot decides its path from the animals it identifies around. Both a parallel implementation of distributed processes and a temporal coding of spiking neurons allow the robot to develop multimodal perception with attentional mecha...

We introduce the Neural Spline, that is a mathematical model built by combining a neural network and an associated Obreshkov polynomial. The neural spline has finite support and can be used as the basic element in constructing continuous modular neural-based models. These models are suitable for function approximation in partitioned domains and are also amenable to efficient parallel or distrib...

A b s t r a c t . In this paper, we propose a new methodology for decomposing pattern classification problems based on the class relations among training data. We also propose two combination principles for integrating individual modules to solve the original problem. By using the decomposition methodology, we can divide a K-class classification problem into (~) relatively smaller two-class cla...