Titlebook: Engineering Applications of Neural Networks; 19th International C Elias Pimenidis,Chrisina Jayne Conference proceedings 2018 Springer Natur

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A Triangle Multi-level Item-Based Collaborative Filtering Method that Improves Recommendations has been widely applied, there are still limitations to be overcome in this research area. Accuracy is still one of the areas that need to be improved. In addition, the rapid growth of information available online presents recommender systems with several challenges. More specifically, data sparsit

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Myo-To-Speech - Evolving Fuzzy-Neural Network Prediction of Speech Utterances from Myoelectric Signaorgans (e.g. the larynx), by neural degeneration or by neurological injury to the motor component of the motor-speech system in the phonation area of the brain (e.g. dysarthria in Parkinson disease). A novel approach to voice rehabilitation consists of predicting the phonetic control sequence of the

Torrid

Model Prediction of Defects in Sheet Metal Forming ProcessesIn this paper, we take a machine learning perspective to choose the best model for defects prediction of sheet metal forming processes. An empirical study is presented with the objective to choose the best machine learning algorithm that will be able to perform accurately this task. For building the

開(kāi)玩笑

Selecting Display Products for Furniture Stores Using Fuzzy Multi-criteria Decision Making Technique accessible and competitive global market. This fact enforces producers to clearly identify and analyze the needs of consumers and to display their products respecting locality based on customers’ needs. The position of the business is strengthened within the market and its competiveness increases b

擋泥板

Conference proceedings 2018n Bristol, UK, in September 2018..The 16 revised full papers and 5 revised short papers presented were carefully reviewed and selected from 39 submissions. The papers are organized in topical sections on?activity recognition,?deep learning,?extreme learning machine, machine learning applications,?pr

micturition

Machine Learning with the Pong Game: A Case Study have been introduced various Machine Learning approaches to solve this problem. This paper gives a summary of some notable techniques to creating a self-learning agent for the Pong game. In addition, it proposes a template for developing this idea into a full-fledged application. An implementation in Java is available online.

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Conference proceedings 2018ions. The papers are organized in topical sections on?activity recognition,?deep learning,?extreme learning machine, machine learning applications,?predictive models, fuzzy and recommender systems,?recurrent neural networks, spiking neural networks..

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1865-0929 39 submissions. The papers are organized in topical sections on?activity recognition,?deep learning,?extreme learning machine, machine learning applications,?predictive models, fuzzy and recommender systems,?recurrent neural networks, spiking neural networks..978-3-319-98203-8978-3-319-98204-5Series ISSN 1865-0929 Series E-ISSN 1865-0937

MILL

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Christian Kahl,Gerald Raj Sundramtable network size. Numerical experiments have been carried out for approximation problems and multi-class classification problems, and preliminary results have shown that the proposed approach works well.