Search results for "Machine"

On the Optimization of Self-Organizing Maps by Genetic Algorithms

1999

Publisher Summary This chapter reviews the research on the genetic optimization of self-organizing maps (SOMs). The optimization of learning rule parameters and of initial weights is able to improve network performance. The latter, however, requires chromosome sizes proportional to the size of the SOM and becomes unwieldy for large networks. The optimization of learning rule structures leads to self-organization processes of character similar to the standard learning rule. A particularly strong potential lies in the optimization of SOM topologies, which allows the study of global dynamical properties of SOMs and related models, as well as to develop tools for their analysis. Hierarchies of …

A Study of the Simulated Evolution of the Spectral Sensitivity of Visual Agent Receptors

2001

In this article we study a model for the evolution of the spectral sensitivity of visual receptors for agents in a continuous virtual environment. The model uses a genetic algorithm (GA) to evolve the agent sensors along with the control of the agents by requiring the agents to solve certain tasks in the simulation environment. The properties of the evolved sensors are analyzed for different scenarios. In particular, it is shown that the GA is able to find a balance between sensor costs and agent performance in such a way that the spectral sensor sensitivity reflects the emission spectrum of the target objects and that the capability of the sensors to evolve can help the agents significantl…

Classification of Sequences with Deep Artificial Neural Networks: Representation and Architectural Issues

2021

DNA sequences are the basic data type that is processed to perform a generic study of biological data analysis. One key component of the biological analysis is represented by sequence classification, a methodology that is widely used to analyze sequential data of different nature. However, its application to DNA sequences requires a proper representation of such sequences, which is still an open research problem. Machine Learning (ML) methodologies have given a fundamental contribution to the solution of the problem. Among them, recently, also Deep Neural Network (DNN) models have shown strongly encouraging results. In this chapter, we deal with specific classification problems related to t…

Bot or not? a case study on bot recognition from web session logs

2018

This work reports on a study of web usage logs to verify whether it is possible to achieve good recognition rates in the task of distinguishing between human users and automated bots using computational intelligence techniques. Two problem statements are given, offline (for completed sessions) and on-line (for sequences of individual HTTP requests). The former is solved with several standard computational intelligence tools. For the second, a learning version of Wald’s sequential probability ratio test is used.

Deep learning for agricultural land use classification from Sentinel-2

2020

[ES] En el campo de la teledetección se ha producido recientemente un incremento del uso de técnicas de aprendizaje profundo (deep learning). Estos algoritmos se utilizan con éxito principalmente en la estimación de parámetros y en la clasificación de imágenes. Sin embargo, se han realizado pocos esfuerzos encaminados a su comprensión, lo que lleva a ejecutarlos como si fueran “cajas negras”. Este trabajo pretende evaluar el rendimiento y acercarnos al entendimiento de un algoritmo de aprendizaje profundo, basado en una red recurrente bidireccional de memoria corta a largo plazo (2-BiLSTM), a través de un ejemplo de clasificación de usos de suelo agrícola de la Comunidad Valenciana dentro d…

The Effects of the Use of Serious Game in Eco-Driving Training

2016

International audience; Serious games present a promising approach to training and learning. The player is engaged in a virtual environment for a purpose beyond pure entertainment, all while having fun. In this paper, we investigate the effects of the use of serious game in eco-driving training. An approach has been developed in order to improve players’ practical skills in terms of eco-driving. This approach is based on the development of a driving simulation based on a serious game, integrating a multisensorial guidance system with metaphors including visual messages (information on fuel consumption, ideal speed area, gearbox management, etc.) and sounds (spatialized sounds, voice message…

Corrigendum to “Predicting service request in support centers based on nonlinear dynamics, ARMA modeling and neural networks” [Expert Systems with Ap…

2013

Predicting service request in support centers based on nonlinear dynamics, ARMA modeling and neural networks

2008

In this paper, we present the use of different mathematical models to forecast service requests in support centers (SCs). A successful prediction of service request can help in the efficient management of both human and technological resources that are used to solve these eventualities. A nonlinear analysis of the time series indicates the convenience of nonlinear modeling. Neural models based on the time delay neural network (TDNN) are benchmarked with classical models, such as auto-regressive moving average (ARMA) models. Models achieved high values for the correlation coefficient between the desired signal and that predicted by the models (values between 0.88 and 0.97 were obtained in th…

Kata Containers: An Emerging Architecture for Enabling MEC Services in Fast and Secure Way

2019

New coming applications will be only possible through Mobile Edge Servers deployed in proximity of the mobile users. Due to the user's mobility and server's workload, service migration will be an integral part of the services. For this reason, a standardized architecture should be designed to accomplish a workload migration in a secure and timely manner. Most research done to date has focused on the use of either virtual machine (VM) or container or a mix of both recently. A final solution might be an architecture only having the advantages of both technologies as the security of the VM and the speed of the containers. Custom solutions, actually, by using both technologies, need continuous …

A genetic approach for adding QoS to distributed virtual environments

2007

Distributed virtual environment (DVE) systems have been designed last years as a set of distributed servers. These systems allow a large number of remote users to share a single 3D virtual scene. In order to provide quality of service in a DVE system, clients should be properly assigned to servers taking into account system throughput and system latency. The latter one is composed of both network and computational delays. This highly complex problem is known as the quality of service (QoS) problem. In this paper, we study the implementation of a genetic algorithm (GA) for solving the QoS problem in DVE systems. Performance evaluation results show that, due to its ability of both finding goo…