Computer Science & Information Technology (CS & IT )最新文献_第2页

CONDITION BASED MAINTENANCE OF TURBINE AND COMPRESSOR OF A CODLAG NAVAL PROPULSION SYSTEM USING DEEP NEURAL NETWORK 基于深度神经网络的舰船推进系统汽轮机和压气机状态维修

Computer Science & Information Technology (CS & IT ) Pub Date : 2019-05-23 DOI: 10.5121/CSIT.2019.90601

Palash Pal, Rituparna Datta, Aviv Segev, Alec Yasinsac

{"title":"CONDITION BASED MAINTENANCE OF TURBINE AND COMPRESSOR OF A CODLAG NAVAL PROPULSION SYSTEM USING DEEP NEURAL NETWORK","authors":"Palash Pal, Rituparna Datta, Aviv Segev, Alec Yasinsac","doi":"10.5121/CSIT.2019.90601","DOIUrl":"https://doi.org/10.5121/CSIT.2019.90601","url":null,"abstract":"System and sub-system maintenance is a significant task for every dynamic system. A plethora of approaches, both quantitative and qualitative, have been proposed to ensure the system safety and to minimize the system downtime. The rapid progress of computing technologies and different machine learning approaches makes it possible to integrate complex machine learning techniques with maintenance strategies to predict system maintenance in advance. The present work analyzes different methods of integrating an Artificial Neural Network (ANN) and ANN with Principle Component Analysis (PCA) to model and predict compressor decay state coefficient and turbine decay state coefficient of a Gas Turbine (GT) mounted on a frigate characterized by a Combined Diesel-Electric and Gas (CODLAG) propulsion plant used in naval vessels. The input parameters are GT parameters and the outputs are GT compressor and turbine decay state coefficients. Due to the presence of a large number of inputs, more hidden layers are required, and as a result a deep neural network is found appropriate. The simulation results confirm that most of the proposed models accomplish the prediction of the decay state coefficients of the gas turbine of the naval propulsion. The results show that a consistently declining hidden layers size which is proportional to the input and to the output outperforms the other neural network architectures. In addition, the results of ANN outperforms hybrid PCAANN in most cases. The ANN architecture design might be relevant to other predictive maintenance systems.","PeriodicalId":372948,"journal":{"name":"Computer Science & Information Technology (CS & IT )","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114448063","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: 5

Dynamic Human-Centered Design:Reinventing Design Philosophies for Advanced Technologies 动态以人为本的设计:为先进技术重塑设计理念

Computer Science & Information Technology (CS & IT ) Pub Date : 2019-04-30 DOI: 10.5121/CSIT.2019.90505

Te-Wei Ho, Timothy Wei, Jing-Ming Wu, F. Lai

引用次数: 0

A Learning Controller Design Approach for A 3-DOF Helicopter System with Online Optimal Control 三自由度直升机系统在线最优控制的学习控制器设计方法

Computer Science & Information Technology (CS & IT ) Pub Date : 2019-04-27 DOI: 10.5121/CSIT.2019.90502

Guilherme Bonfim De Sousa, Janes V. R.Lima, Patrícia Helena M. Rêgo, Alain G.Souza, J. V. FonsecaNeto

引用次数: 0

ON-LINE OPTIMIZATION METHOD FOR ENERGY EFFICIENT PUMP-STORAGE OPERATION WITH INTEGRATED FILLING TIME CONSTRAINT 综合加注时间约束下的高效抽水蓄能在线优化方法

Computer Science & Information Technology (CS & IT ) Pub Date : 2019-04-27 DOI: 10.5121/CSIT.2019.90506

Thomas Hieninger, F. Goppelt, Ronald Schmidt-Vollus

引用次数: 2

Method for the Detection of Carrierin-Carrier Signals Based on Fourth-Order Cumulants 基于四阶累积量的载波-载波信号检测方法

Computer Science & Information Technology (CS & IT ) Pub Date : 2019-04-27 DOI: 10.5121/CSIT.2019.90503

V. Semenov, P. Omelchenko, O. Kruhlyk

引用次数: 0

Consent Based Access Policy Framework 基于同意的访问策略框架

Computer Science & Information Technology (CS & IT ) Pub Date : 2019-04-27 DOI: 10.5121/CSIT.2019.90504

Geetha Madadevaiah, R. Prasad, Amogh Hiremath, M. Dumontier, A. Dekker

引用次数: 0

Evolutionary Algorithms to Simulate Real Conditions in Artificial Intelligence as Basis for Mathematical Fuzzy Clustering 人工智能中模拟真实情况的进化算法作为数学模糊聚类的基础

Computer Science & Information Technology (CS & IT ) Pub Date : 2019-04-27 DOI: 10.5121/CSIT.2019.90501

Ness

{"title":"Evolutionary Algorithms to Simulate Real Conditions in Artificial Intelligence as Basis for Mathematical Fuzzy Clustering","authors":"Ness","doi":"10.5121/CSIT.2019.90501","DOIUrl":"https://doi.org/10.5121/CSIT.2019.90501","url":null,"abstract":"In present-day physics we may assume space as a perfect continuum describable by discrete mathematics or a set of discrete elements described by a programmed probabilistic process or find alternative models that grasp real conditions better as they more closely simulate real behaviour. Clustering logic based on evolutionary algorithms is able to give meaning to unlimited amounts of data that enterprises generate and that contain valuable hidden knowledge. Evolutionary algorithms are useful to make sense of this hidden knowledge, as they are very close to nature and the mind. However, most known applications of evolutionary algorithms cluster data points to one group, thereby leaving key aspects to understand the data out and thus hardening simulations of biological processes. Fuzzy clustering methods divide data points into groups based on item similarity and detects patterns between items in a set, whereby data points can belong to more than one group. Evolutionary algorithm fuzzy clustering inspired multivariate mechanism allows for changes at each iteration of the algorithm and improves performance from one feature to another and from one cluster to another. It is applicable to real life objects that are neither circular nor elliptical and thereby allows for clusters of any predefined shape. \u0000In this paper we explain the philosophical concept of evolutionary algorithms for production of fuzzy clustering methods that produce good quality of clustering in the fields of virtual reality, augmented reality and gaming applications and in industrial manufacturing, robotic assistants, product development, law and forensics as well as parameterless body model extraction from CCTV camera images.","PeriodicalId":372948,"journal":{"name":"Computer Science & Information Technology (CS & IT )","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132422138","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

SOLVING THE CHINESE PHYSICAL PROBLEM BASED ON DEEP LEARNING AND KNOWLEDGE GRAPH 基于深度学习和知识图谱的中文物理问题求解

Computer Science & Information Technology (CS & IT ) Pub Date : 2019-03-23 DOI: 10.5121/CSIT.2019.90310

Mingchen Li, Zili Zhou, Yanna Wang

{"title":"SOLVING THE CHINESE PHYSICAL PROBLEM BASED ON DEEP LEARNING AND KNOWLEDGE GRAPH","authors":"Mingchen Li, Zili Zhou, Yanna Wang","doi":"10.5121/CSIT.2019.90310","DOIUrl":"https://doi.org/10.5121/CSIT.2019.90310","url":null,"abstract":"In recent years, problem solving, automatic proof and human-like test-tasking have become a hot spot of research. This paper focus on the study of solving physical problem in Chinese. Based on the analysis of physical corpus, it is found that the physical problem are made up of n-tuples which contain concepts and relations between concepts, and the n-tuples can be expressed in the form of UP-graph (The graph of understanding problem), which is the semantic expression of physical problem. UP-graph is the base of problem solving which is generated by using physical knowledge graph (PKG). However, current knowledge graph is hard to be used in problem solving, because it cannot store methods for solving problem. So this paper presents a model of PKG which contains concepts and relations, in the model, concepts and relations are split into terms and unique IDs, and methods can be easily stored in the PKG as concepts. Based on the PKG, DKP-solving is proposed which is a novel approach for solving physical problem. The approach combines rules, statistical methods and knowledge reasoning effectively by integrating the deep learning and knowledge graph. The experimental results over the data set of real physical text indicate that DKP-solving is effective in physical problem solving.","PeriodicalId":372948,"journal":{"name":"Computer Science & Information Technology (CS & IT )","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116857981","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

INTERSECTION TYPE SYSTEM AND LAMBDA CALCULUS WITH DIRECTOR STRINGS 交集类型系统和λ演算与导演字符串

Computer Science & Information Technology (CS & IT ) Pub Date : 2019-03-23 DOI: 10.5121/CSIT.2019.90313

X. Shen, Kougen Zheng

引用次数: 0

OCCLUSION HANDLED BLOCK-BASED STEREO MATCHING WITH IMAGE SEGMENTATION 闭塞处理基于块的立体匹配与图像分割

Computer Science & Information Technology (CS & IT ) Pub Date : 2019-03-23 DOI: 10.5121/CSIT.2019.90303

Jisu Kim, Cheolhyeong Park, Ju O. Kim, Deokwoo Lee

引用次数: 0