Adv. Artif. Neural Syst.最新文献_第4页

Application of Neural Network Modeling to Identify Auditory Processing Disorders in School-Age Children 应用神经网络模型识别学龄儿童听觉加工障碍

Adv. Artif. Neural Syst. Pub Date : 2015-01-01 DOI: 10.1155/2015/635840

S. Krishnamurti

引用次数: 3

Artificial Neural Network Estimation of Thermal Insulation Value of Children's School Wear in Kuwait Classroom 科威特教室儿童校服保温值的人工神经网络估算

Adv. Artif. Neural Syst. Pub Date : 2015-01-01 DOI: 10.1155/2015/421215

Khaled Al-Rashidi, R. Alazmi, M. Alazmi

{"title":"Artificial Neural Network Estimation of Thermal Insulation Value of Children's School Wear in Kuwait Classroom","authors":"Khaled Al-Rashidi, R. Alazmi, M. Alazmi","doi":"10.1155/2015/421215","DOIUrl":"https://doi.org/10.1155/2015/421215","url":null,"abstract":"Artificial neural network (ANN) was utilized to predict the thermal insulation values of children's school wear in Kuwait. The input thermal insulation data of the different children's school wear used in Kuwait classrooms were obtained from study using thermal manikins. The lowest mean squared error (MSE) value for the validation data was 1.5 × 10-5 using one hidden layer of six neurons and one output layer. The R2 values for the training, validation, and testing data were almost equal to 1. The values from ANN prediction were compared with McCullough's equation and the standard tables' methods. Results suggested that the ANN is able to give more accurate prediction of the clothing thermal insulation values than the regression equation and the standard tables methods. The effect of the different input variables on the thermal insulation value was examined using Garson algorithm and sensitivity analysis and it was found that the cloths weight, the body surface area nude (BSA0), and body surface area covered by one layer of clothing (BSAC1) have the highest effect on the thermal insulation value with about 29%, 27%, and 23%, respectively.","PeriodicalId":7288,"journal":{"name":"Adv. Artif. Neural Syst.","volume":"20 1","pages":"421215:1-421215:9"},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78472544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Generalisation over Details: The Unsuitability of Supervised Backpropagation Networks for Tetris 细节上的泛化:监督反向传播网络在俄罗斯方块中的不适用性

Adv. Artif. Neural Syst. Pub Date : 2015-01-01 DOI: 10.1155/2015/157983

Ian J. Lewis, Sebastian L. Beswick

引用次数: 2

Water Quality Modeling in Reservoirs Using Multivariate Linear Regression and Two Neural Network Models 基于多元线性回归和两种神经网络模型的水库水质建模

Adv. Artif. Neural Syst. Pub Date : 2015-01-01 DOI: 10.1155/2015/521721

Wei-Bo Chen, Wen‐Cheng Liu

引用次数: 67

Sensorless Direct Power Control of Induction Motor Drive Using Artificial Neural Network 基于人工神经网络的感应电机无传感器直接功率控制

Adv. Artif. Neural Syst. Pub Date : 2014-11-13 DOI: 10.1155/2015/318589

A. H. Niasar, Hossein Rahimi Khoei

引用次数: 21

Long Time Behavior for a System of Differential Equations with Non-Lipschitzian Nonlinearities 一类非lipschitzian非线性微分方程组的长时间行为

Adv. Artif. Neural Syst. Pub Date : 2014-01-01 DOI: 10.1155/2014/252674

N. Tatar

引用次数: 4

Global Stability, Bifurcation, and Chaos Control in a Delayed Neural Network Model 时滞神经网络模型的全局稳定性、分岔和混沌控制

Adv. Artif. Neural Syst. Pub Date : 2014-01-01 DOI: 10.1155/2014/369230

Amitava Kundu, P. Das

引用次数: 2

An Electronic Circuit Model of the Interpostsynaptic Functional LINK Designed to Study the Formation of Internal Sensations in the Nervous System 研究神经系统内部感觉形成的突触后功能连接的电子电路模型

Adv. Artif. Neural Syst. Pub Date : 2014-01-01 DOI: 10.1155/2014/318390

K. Vadakkan

{"title":"An Electronic Circuit Model of the Interpostsynaptic Functional LINK Designed to Study the Formation of Internal Sensations in the Nervous System","authors":"K. Vadakkan","doi":"10.1155/2014/318390","DOIUrl":"https://doi.org/10.1155/2014/318390","url":null,"abstract":"The nervous system makes changes in response to the continuous arrival of associative learning stimuli from the environment and executes behavioral motor activities after making predictions based on past experience. The system exhibits dynamic plasticity changes that involve the formation of the first-person internal sensations of perception, memory, and consciousness to which only the owner of the nervous system has access. These properties of natural intelligence need to be verified for their mechanism of formation using engineered systems so that a third person can access them. In the presence of a synaptic junctional delay of up to two milliseconds, we anticipate that the systems property of formation of internal sensations is likely independent of the mode of conduction along the neuronal processes. This allows testing for the formation of internal sensations using electronic circuits. The present work describes the neurobiological context for the formation of the basic units of inner sensations that occur through the reactivation of interpostsynaptic functional LINKs and its connection to motor activity. These mechanisms are translated to an analogue circuit unit for the development of robotic systems.","PeriodicalId":7288,"journal":{"name":"Adv. Artif. Neural Syst.","volume":"3 2 1","pages":"318390:1-318390:15"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90716506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Architecture Analysis of an FPGA-Based Hopfield Neural Network 基于fpga的Hopfield神经网络结构分析

Adv. Artif. Neural Syst. Pub Date : 2014-01-01 DOI: 10.1155/2014/602325

Miguel Angelo de Abreu de Sousa, E. Horta, S. Kofuji, E. Del-Moral-Hernandez

引用次数: 5

Oscillatory Behavior on a Three-Node Neural Network Model with Discrete and Distributed Delays 具有离散和分布延迟的三节点神经网络模型的振荡行为

Adv. Artif. Neural Syst. Pub Date : 2014-01-01 DOI: 10.1155/2014/536324

C. Feng

引用次数: 4