Recent Trends in Computational Intelligence最新文献

Boundary Element Modeling and Optimization of Three Temperature Nonlinear Fractional Generalized Photo-Thermoelastic Interaction in Anisotropic Semiconductor Structures 各向异性半导体结构中三温度非线性分数阶广义光-热弹性相互作用的边界元建模与优化

Recent Trends in Computational Intelligence Pub Date : 2020-03-25 DOI: 10.5772/intechopen.91230

M. Fahmy

{"title":"Boundary Element Modeling and Optimization of Three Temperature Nonlinear Fractional Generalized Photo-Thermoelastic Interaction in Anisotropic Semiconductor Structures","authors":"M. Fahmy","doi":"10.5772/intechopen.91230","DOIUrl":"https://doi.org/10.5772/intechopen.91230","url":null,"abstract":"The main objective of this paper is to introduce a new fractional-order theory called nonlinear fractional generalized photo-thermoelasticity involving three temperatures. Due to strong nonlinearity, it is very difficult to solve the wave problems related to this theory analytically. Therefore, we propose a new boundary element algorithm and technique for simulation and optimization of the considered problems related to this theory. The genetic algorithm (GA) as an optimization method has been applied based on free form deformation (FFD) technique to improve the performance of our proposed technique. In the formulation of the considered problem, the profiles of the considered objects are determined by FFD technique, where the FFD control point positions are treated as genes, and then the chromosome profiles are defined with the gene sequence. The population is established by a number of individuals (chromosomes), where the objective functions of individuals are achieved by the boundary element method (BEM). A nonuniform rational B-spline curve (NURBS) was used to model optimized boundary where it reduces the number of control points and provides the flexibility to design several different shapes for solving the considered photo-thermoelastic wave problems. The numerical results verify the validity and accuracy of our proposed boundary element technique.","PeriodicalId":183051,"journal":{"name":"Recent Trends in Computational Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131135096","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

Categorizing Patient Disease into ICD-10 with Deep Learning for Semantic Text Classification 基于深度学习的语义文本分类将患者疾病分类为ICD-10

Recent Trends in Computational Intelligence Pub Date : 2020-02-28 DOI: 10.5772/intechopen.91292

J. Zhong, X. Yi

引用次数: 2

Deep Learning Approach to Key Frame Detection in Human Action Videos 人类动作视频关键帧检测的深度学习方法

Recent Trends in Computational Intelligence Pub Date : 2020-02-12 DOI: 10.5772/intechopen.91188

U. Gawande, K. Hajari, Yogesh Golhar

引用次数: 11

Using Discrete Geometric Models in an Automated Layout 在自动布局中使用离散几何模型

Recent Trends in Computational Intelligence Pub Date : 2020-01-30 DOI: 10.5772/intechopen.90941

L. Markin

{"title":"Using Discrete Geometric Models in an Automated Layout","authors":"L. Markin","doi":"10.5772/intechopen.90941","DOIUrl":"https://doi.org/10.5772/intechopen.90941","url":null,"abstract":"The application of discrete (voxel) geometric models in computer-aided design problems is shown. In this case, the most difficult formalized task of computer-aided design is considered—computer-aided layout. The solution to this problem is most relevant when designing products with a high density of layout (primarily transport equipment). From a mathematical point of view, these are placement problems; therefore, their solution is based on the use of a geometric modeling apparatus. The basic provisions and features of discrete modeling of geometric objects, their place in the system of geometric modeling, the advantages and disadvantages of discrete geometric models, and their primary use are described. Their practical use in solving some of the practical problems of automated layout is shown. This is the definition of the embeddability of the placed objects and the task of tracing and evaluating the shading. Algorithms and features of their practical implementation are described. A numerical assessment of the accuracy and performance of the developed geometric modeling algorithms shows the possibility of their implementation even on modern computers of medium power. This allows us to hope for the integration of the developed layout algorithms into modern systems of solid-state geometric modeling in the form of plug-ins.","PeriodicalId":183051,"journal":{"name":"Recent Trends in Computational Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128397532","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: 0

Classification Problem in Imbalanced Datasets 不平衡数据集的分类问题

Recent Trends in Computational Intelligence Pub Date : 2019-12-09 DOI: 10.5772/intechopen.89603

A. Mahani, Ahmed Riad Baba Ali

引用次数: 11

Effective Pitch Value Detection in Noisy Intelligent Environments for Efficient Natural Language Processing 基于噪声智能环境的高效自然语言处理中基音值检测

Recent Trends in Computational Intelligence Pub Date : 2019-10-17 DOI: 10.5772/intechopen.89697

D. Vlaj, A. Zgank, M. Kos

{"title":"Effective Pitch Value Detection in Noisy Intelligent Environments for Efficient Natural Language Processing","authors":"D. Vlaj, A. Zgank, M. Kos","doi":"10.5772/intechopen.89697","DOIUrl":"https://doi.org/10.5772/intechopen.89697","url":null,"abstract":"The performance of applications based on natural language processing depends primarily on the environment in which these applications are applied. Intelligent environments will be one of the major applications used to process natural language. The methods for speaker ’ s gender classification can adapt and improve the performance of natural language processing applications. That is why, this chapter will present an effective speaker ’ s pitch value detection in noisy environments, which then allows more robust speaker ’ s gender classification. The chapter presents the algorithm for the speaker ’ s pitch value detection and performs the comparison in various noisy environments. The experiments are carried out on the part of the publically available Aurora 2 speech database. The results showed that the automatically determined pitch values deviate, on average, only by 8.39 Hz from the reference pitch value. A well-defined pitch value allows a functional speaker ’ s gender classification. In this chapter, presented speaker ’ s gender classification works well, even at low signal to noise ratios. The experiments show that the speaker ’ s gender classification performance at SNR 0 dB is higher than 91% when the automatically determined pitch value is used. Speaker ’ s gender classification can then be used further in the processes of natural language processing.","PeriodicalId":183051,"journal":{"name":"Recent Trends in Computational Intelligence","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131137162","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: 0

Machine Translation and the Evaluation of Its Quality 机器翻译及其质量评价

Recent Trends in Computational Intelligence Pub Date : 2019-09-07 DOI: 10.5772/intechopen.89063

M. Maučec, G. Donaj

引用次数: 14