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Information Processing in Agriculture 2019年第3期6卷 316-325页

作者： Mohamad M.Awad National Council for Scientific Research RemoteSensing CenterP.O.Box 11-8281BeirutLebanon

There are many crop yield estimation techniques which are used in countries around the world,but the most effective is the one based on remote sensing data and ***,remote sensing data which are needed to estimate crop yield is incomplete most of the time due to many obstacles such as climate conditions(percentage of cloud cover),and low temporal *** problems reduce the effectiveness of the known crop yield estimation techniques and render them *** was many attempts to solve these problems by using high temporal resolution and low spatial resolution ***,this type of images are suitable for very large homogeneous crop *** compensate for the lack of high spatial resolution satellite images,a new mathematical model is *** on the new mathematical model an intelligent system is implemented that includes the use of energy balance equation to improve the crop yield *** verify the results of the intelligent system,several farmers are interviewed and information about their crops yield is *** comparison between the estimated crop yield and the actual production in different fields proves the high accuracy of the intelligent system.

关键词： Crop yield Environment Remote sensing Image processing Evapotranspiration intelligent system

An intelligent system for calculating the scale of rational,enlarged production of an underground non-ferrous metal mine

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Journal of China University of Mining and Technology 2008年第2期18卷 214-219页

作者： ZHENG Ming-gui CAI Si-jing Civil ＆ Environment Engineering School University of Science and Technology Beijing Beijing 100083 China

The enlarged production scale of underground non-ferrous metal mines is affected by many uncertain factors difficult to describe mathematically with any level of *** problem can be solved by a synthesis of artificial *** on the analysis of the major factors affecting the scale of enlarged production,we first interpreted in detail the design principles and structure of the intelligent ***,we introduced an ANN *** order to ensure technological and scale efficien- cies of the training samples for ANN,we filtrated the samples with a DEA ***,we trained the intelligent system,which was proved to be very efficient.

关键词： non-ferrous metal mines production scale enlarge intelligent system ANN

An intelligent system for Analysing Manas Prakrti in Human Resource Management

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Journal of Literature and Art Studies 2015年第4期5卷 301-306页

作者： D.S. Kalana Mendis Department of Information Technology Advanced Technological Institute Dehiwala Sri Lanka

Human resource management is said to be the importance of spiritual, ethical, and human values that condition human behaviour. The immediate problem that it poses for a full understanding of human functioning is that the inner subjective experiences of consciousness based on human resource management. Ayurveda occupies the heights of human psychological accomplishment and could usefully call upon the insights of any of these sources to aid in addressing the problematic nature of modern-day businesses and have significant bearing on human behaviour. Manas prakrti in Ayuverda contributes to the study of personality. Tamas-Rajas-Sattva temperamental groups give rise to the framework of Space-Time-Causation when evolution starts in association with Consciousness Principle in manas prakrti. In this paper I present a methodology to analyze Temperamental groups that are found in manas prakrti by using an intelligent system. This will guide understand, instrumental values, operating values, and weak values of employees in human resource management.

关键词： Ayurveda manas prakrti temperamental groups intelligent system human resource management

intelligent recognition system for viewpoint variations on gait and speech using CNN-CapsNet

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International Journal of intelligent Computing and Cybernetics 2022年第3期15卷 363-382页

作者： G.Merlin Linda N.V.S.Sree Rathna Lakshmi N.Senthil Murugan Rajendra Prasad Mahapatra V.Muthukumaran M.Sivaram Department of Computer Science and Engineering SRM Institute of Science and Technology–Vadapalani CampusChennaiIndia Department of Electronics and Communication Engineering Agni College of TechnologyChennaiIndia School of Computer Science and Engineering VIT-AP UniversityAmaravatiIndia Department of Computer Science and Engineering SRM Institute of Science and TechnologyGhaziabadIndia Department of Mathematics School of Applied SciencesREVA UniversityBangaloreIndia Faculty of Information Technology Ton Duc Thang UniversityHo Chi Minh CityVietnam

Purpose-The paper aims to introduce an intelligent recognition system for viewpoint variations of gait and *** proposes a convolutional neural network-based capsule network(CNN-CapsNet)model and outlining the performance of the system in recognition of gait and speech *** proposed intelligent system mainly focuses on relative spatial hierarchies between gait features in the entities of the image due to translational invariances in sub-sampling and speech ***/methodology/approach-This proposed work CNN-CapsNet is mainly used for automatic learning of feature representations based on CNNand used capsule vectors as neurons to encode all the spatial information of an image by adapting equal variances to change in *** proposed study will resolve the discrepancies caused by cofactors and gait recognition between opinions based on a model of ***-This research work provides recognition of signal,biometric-based gait recognition and sound/speech *** evaluations are conducted on three aspects of scenarios,namely fixed-view,cross-view and multi-view *** main parameters for recognition of gait are speed,change in clothes,subjects walking with carrying object and intensity of *** limitations/implications-The proposed CNN-CapsNet has some limitations when considering for detecting the walking targets from surveillance videos considering multimodal fusion approaches using hardware sensor *** can also act as a pre-requisite tool to analyze,identify,detect and verify the malware *** implications-This research work includes for detecting the walking targets from surveillance videos considering multimodal fusion approaches using hardware sensor *** can also act as a pre-requisite tool to analyze,identify,detect and verify the malware ***/value-This proposed research work proves to be performing better for the recognition of gait and speech when

关键词： intelligent system Gait recognition Convolutional neural network Deep learning Capsule network Viewpoint variations

Multi-Sensor intelligent system for On-Line and Real-Time Moneitoring Tool Cutting State in FMS

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Journal of Beijing Institute of Technology 1997年第3期6卷 258-266页

作者：徐春广王信义邢济收杨大勇北京理工大学机械工程与自动化学院

The principle and the constitution of an intelligent system for on-line and real-time montitoring tool cutting state were discussed and a synthetic sensors schedule combined a new type fluid acoustic emission sensor (AE) with motor current sensor was presented. The parallel communication between control system of machine tools, the monitoring intelligent system,and several decision-making systems for identifying tool cutting state was established It can auto - matically select the sensor way ,monitoring mode and identifying method in machining process- ing so as to build a successful and effective intelligent system for on -line and real-time moni- toring cutting tool states in FMS.

关键词： tool cutting state on-line monitoring intelligent system acoustic emission sensor

intelligent systems and Photovoltaic Cells Empowered Topologically by Sudoku Networks

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Computers, Materials & Continua 2023年第2期74卷 4221-4238页

作者： Khalid Hamid Muhammad Waseem Iqbal MUsman Ashraf Akber Abid Gardezi Shafiq Ahmad Mejdal Alqahtani Muhammad Shafiq Department of Computer Science Superior UniversityLahore54000Pakistan Department of Software Engineering Superior UniversityLahore54000Pakistan Department of Computer Science GC Women UniversitySialkot51310Pakistan Department of Computer Science COMSATS University IslamabadIslamabad45550Pakistan Industrial Engineering Department College of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

A graph invariant is a number that can be easily and uniquely calculated through a ***,part of mathematical graph invariants has been portrayed and utilized for relationship ***,no reliable appraisal has been embraced to pick,how much these invariants are associated with a network graph in interconnection networks of various fields of computer science,physics,and *** this paper,the study talks about sudoku networks will be networks of fractal nature having some applications in computer science like sudoku puzzle game,intelligent systems,Local area network(LAN)development and parallel processors interconnections,music composition creation,physics like power generation interconnections,Photovoltaic(PV)cells and chemistry,synthesis of chemical *** networks are generally utilized in disorder,fractals,recursive groupings,and complex *** outcomes are the normal speculations of currently accessible outcomes for specific classes of such kinds of networks of two unmistakable sorts with two invariants K-banhatti sombor(KBSO)invariants,Irregularity sombor(ISO)index,Contraharmonic-quadratic invariants(CQIs)and dharwad invariants with their reduced *** study solved the Sudoku network used in mentioned systems to improve the performance and find irregularities present in *** calculated outcomes can be utilized for the modeling,scalability,introduction of new architectures of sudoku puzzle games,intelligent systems,PV cells,interconnection networks,chemical compounds,and extremely huge scope in very large-scale integrated circuits(VLSI)of processors.

关键词： Sudoku dharwad KBSO indices CQIs network graph intelligent system photovoltaic cells

An intelligent Neural Networks system for Adaptive Learning and Prediction of a Bioreactor Benchmark Process

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Chinese Journal of Chemical Engineering 2008年第1期16卷 62-66页

作者：邹志云于德弘冯文强于鲁平郭宁 School of Mechanical Engineering Xi＇an Jiaotong University Xi＇an 710049 China Beijing Research Institute of Pharmaceutical Chemistry Beijing 102205 China

The adaptive learning and prediction of a highly nonlinear and time-varying bioreactor benchmark process is studied using Neur-On-Line, a graphical tool kit for developing and deploying neural networks in the G2 real time intelligent environment,and a new modified Broyden, Fletcher, Goldfarb, and Shanno （BFGS） quasi-Newton algorithm. The modified BFGS algorithm for the adaptive learning of back propagation （BP） neural networks is developed and embedded into NeurOn-Line by introducing a new search method of learning rate to the full memory BFGS algorithm. Simulation results show that the adaptive learning and prediction neural network system can quicklv track the time-varving and nonlinear behavior of the bioreactor.

关键词： intelligent system neural networks adaptive learning adaptive prediction bioreactor process

Unified stabilizing controller synthesis approach for discrete-time intelligent systems with time delays by dynamic output feedback

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Science in China(Series F) 2007年第4期50卷 636-656页

作者： LIU MeiQin College of Electrical Engineering Zhejiang University Hangzhou 310027 China

A novel model, termed the standard neural network model （SNNM）, is advanced to describe some delayed （or non-delayed） discrete-time intelligent systems composed of neural networks and Takagi and Sugeno （T-S） fuzzy models. The SNNM is composed of a discrete-time linear dynamic system and a bounded static nonlinear operator. Based on the global asymptotic stability analysis of the SNNMs, linear and nonlinear dynamic output feedback controllers are designed for the SNNMs to stabilize the closed-loop systems, respectively. The control design equations are shown to be a set of linear matrix inequalities （LMIs） which can be easily solved by various convex optimization algorithms to determine the control signals. Most neural-network-based （or fuzzy） discrete-time intelligent systems with time delays or without time delays can be transformed into the SNNMs for controller synthesis in a unified way. Three application examples show that the SNNMs not only make controller synthesis of neural-network-based （or fuzzy） discrete-time intelligent systems much easier, but also provide a new approach to the synthesis of the controllers for the other type of nonlinear systems.

关键词： standard neural network model (SNNM) linear matrix inequality (LMI) intelligent system asymptotic stability output feedback control time delay discrete-time chaotic neural network Takagi and Sugeno (T-S) fuzzy model

Research on the intelligent Decision-making Support system of Securities

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Research on the Intelligent Decision-making Support System o...

Design and implementation of intelligent mobile information system for campus safety management

第17届工业工程与工程管理国际学术会议(IE&EM2010)

作者： Fei DING School of Management,Wuhan University of Technology,Wuhan,China

It is an urgent task for securities investment managers to enhance their securities investment decision-making by taking advantage of artificial *** paper aims to build an intelligent securities investment decision-making support system,and uses data-driven decision-making support methodology to conduct an in-depth analysis of the prominent issues in knowledge-based securities investment decision-making *** of the research achievements described in this paper have been applied to my company,passed evaluation by an expert panel,and devoted to practical purposes,with significant results achieved.

关键词： intelligent system securities investment decision-making support

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Design and implementation of intelligent mobile information ...