Analysis of Tourism Demand Difference Based on Data Mining and Intelligent Analysis

To serve as a reference for future foreign tourism study,relevant tourist sectors have done in-depth investigations on foreign tourism both domestically and internationally.A study of outbound tourism activities from the viewpoint of tourists can examine its development law and create successful marketing tactics based on the rise in the number of foreign tourists.Based on this,this study suggests a data mining technique to examine the variations in travel needs and marketing tactics among various consumer groups.The combined example analysis demonstrates how logical and useful our data mining analysis is.Our data tests demonstrate that the tourism strategy outlined in this paper can enhance the number of tourists by piquing their interest based on the rise in the number of international travellers travelling overseas.

Analysis of Technical Intelligence of Tumor Cell Therapy Based on Patent Map

Objective To analyze the technical information in the field of tumor cell therapy in China,and to provide reference for identifying technical trends and predicting technical opportunities.Methods Based on the patent data in the field of tumor cell therapy in China,the patent map method was used to construct a scientific technical information analysis model.Then,the technical status of new drug research and development in this field was explored to identify technical opportunities.Results and Conclusion Studies have found that China’s tumor immunotherapy is in the growth stage.The technical innovation regions are mainly distributed in the east and innovative entities are enterprises.Technology hotspots are concentrated in areas such as A61P35,C12N5,and the patented technical efficacy is high.Besides,the technical research and development opportunities identified are closely related to the background in this field.To better promote the development of the industry,enterprises and research institutions should strengthen cooperation in technological innovation Meanwhile,they should pay attention to technical efficacy analysis to identify more technical opportunities,thereby effectively guiding innovation strategic decisions.

Intelligent back analysis of geotechnical parameters for time-dependent rock mass surrounding mine openings using grey Verhulst model

In this paper,we present a new method of intelligent back analysis(IBA)using grey Verhulst model(GVM)to identify geotechnical parameters of rock mass surrounding tunnel,and validate it via a test for a main openings of−600 m level in Coal Mine“6.13”,Democratic People's Republic of Korea.The displacement components used for back analysis are the crown settlement and sidewalls convergence monitored at the end of the openings excavation,and the final closures predicted by GVM.The non-linear relation between displacements and back analysis parameters was obtained by artificial neural network(ANN)and Burger-creep viscoplastic(CVISC)model of FLAC3D.Then,the optimal parameters were determined for rock mass surrounding tunnel by genetic algorithm(GA)with both groups of measured displacements at the end of the final excavation and closures predicted by GVM.The maximum absolute error(MAE)and standard deviation(Std)between calculated displacements by numerical simulation with back analysis parameters and in situ ones were less than 6 and 2 mm,respectively.Therefore,it was found that the proposed method could be successfully applied to determining design parameters and stability for tunnels and underground cavities,as well as mine openings and stopes.

Intelligent Resources Management System Design in Information Centric Networking

Information centric networking(ICN) is a new network architecture that is centred on accessing content. It aims to solve some of the problems associated with IP networks, increasing content distribution capability and improving users' experience. To analyse the requests' patterns and fully utilize the universal cached contents, a novel intelligent resources management system is proposed, which enables effi cient cache resource allocation in real time, based on changing user demand patterns. The system is composed of two parts. The fi rst part is a fi ne-grain traffi c estimation algorithm called Temporal Poisson traffi c prediction(TP2) that aims at analysing the traffi c pattern(or aggregated user requests' demands) for different contents. The second part is a collaborative cache placement algorithm that is based on traffic estimated by TP2. The experimental results show that TP2 has better performance than other comparable traffi c prediction algorithms and the proposed intelligent system can increase the utilization of cache resources and improve the network capacity.

A Survey on Methods and Applications of Intelligent Market Basket Analysis Based on Association Rule

The market trends rapidly changed over the last two decades.The primary reason is the newly created opportunities and the increased number of competitors competing to grasp market share using business analysis techniques.Market Basket Analysis has a tangible effect in facilitating current change in the market.Market Basket Analysis is one of the famous fields that deal with Big Data and Data Mining applications.MBA initially uses Association Rule Learning(ARL)as a mean for realization.ARL has a beneficial effect in providing a plenty benefit in analyzing the market data and understanding customers’behavior.An important motive of using such techniques is maximizing the business profit as well as matching the exact customer needs as closely as possible.In this survey paper,we discussed several applications and methods of MBA based on ARL.Also,we reviewed some association rule learning measurements including trust,lift,leverage,and others.Furthermore,we discuss some open issues and future topics in the area of market basket analysis and association rule learning.

Displacement-based back analysis of mitigating the effects of displacement loss in underground engineering

Displacement-monitoring-based back analysis is a popular method for geomechanical parameter estimation.However,due to the delayed installation of multi-point extensometers,the monitoring curve is only a part of the overall one,leading to displacement loss.Besides,the monitoring and construction time on the monitoring curve is difficult to determine.In the literature,the final displacement was selected for the back analysis,which could induce unreliable results.In this paper,a displacement-based back analysis method to mitigate the influence of displacement loss is developed.A robust hybrid optimization algorithm is proposed as a substitute for time-consuming numerical simulation.It integrates the strengths of the nonlinear mapping and prediction capability of the support vector machine(SVM)algorithm,the global searching and optimization characteristics of the optimized particle swarm optimization(OPSO)algorithm,and the nonlinear numerical simulation capability of ABAQUS.To avoid being trapped in the local optimum and to improve the efficiency of optimization,the standard PSO algorithm is improved and is compared with other three algorithms(genetic algorithm(GA),simulated annealing(SA),and standard PSO).The results indicate the superiority of OPSO algorithm.Finally,the hybrid optimization algorithm is applied to an engineering project.The back-analyzed parameters are submitted to numerical analysis,and comparison between the calculated and monitoring displacement curve shows that this hybrid algorithm can offer a reasonable reference for geomechanical parameters estimation.

Method and application of knowledge organization system for S&T literature

In the big data environment, the construction of massive S&T literature data resources needs intelligent technical assistance. With a focus on comparing the domestic and foreign knowledge organization systems and their applications, this article analyzes and summarizes the gaps in related researches and applications at home and abroad. A knowledge organization system framework for S&T literature data resources is presented in the article. Starting from the basic element of knowledge organization system, it also proposes and designs terminology-based analysis methods and technologies for S&T literature. Based on this framework, it proposes ideas and develops corresponding software tool to carry out relevant experiments. It gives an overview of theories and technologies method for future research.

The Intelligent Teaching Resource Program： Applications to Writing

This paper examined the computer-assisted TRP （Teaching Resource Program）, which is an intelligent writing program. Different from previous research, this study emphasized TRP＇s integrative and holistic functions of intelligent analysis, intelligent scoring, and intelligent comment on writing pieces. In what follows, this paper conducted a study of intelligent essay scoring system related to intelligent analysis, intelligent scoring, and intelligent comment of the writing pieces. Also, this paper provided a literature review of existing computer-assisted essay scoring systems and analyzed the advantages and disadvantages of them. Based on these findings in our research, we can conclude that the integrative and holistic computer-assisted TRP can effectively analyze, score, and comment essays, consequently enhancing the writing performance. Some useful implications from this study include that the computer-assisted TRP should be further integrated with writing learning and instruction

Research of recognizing intelligence based on commanding decision-making

In commanding decision-making, the commander usually needs to know a lot of situations（intelligence） on the adversary. Because of the military intelligence with opposability, it is inevitable that intelligence personnel take some deceptive information released by the rival as intelligence data in the process of intelligence gathering. Since the failure of intelligence is likely to lead to a serious aftereffect, the recognition of intelligence is a very important problem. An elementary research on recognizing military intelligence and puts forward a systematic processing method are made. First, the types and characteristics of military intelligence are briefly discussed, a research thought of recognizing military intelligence by means of recognizing military hypotheses are presented. Next, the reasoning mode and framework for recognizing military hypotheses are presented from the angle of psychology of intelligence analysis and non-monotonic reasoning. Then, a model for recognizing military hypothesis is built on the basis of fuzzy judgement information given by intelligence analysts. A calculative example shows that the model has the characteristics of simple calculation and good maneuverability. Last, the methods that selecting the most likely hypothesis from the survival hypotheses via final recognition are discussed.

Optimal video communication strategy for intelligent video analysis in unmanned aerial vehicle applications

For Unmanned Aerial Vehicles(UAV),the intelligent video analysis is a key technology in intelligent autonomous control,real-time navigation and surveillance.However,poor UAV wireless links would degrade the quality of video communication,leading to difficulties in video analysis.To meet the challenges of packet-loss and limited bandwidth in adverse UAV channel environments,this paper proposes a parameter optimization mechanism for UAV intelligent video analysis.In the proposed method,an Optimal Strategy Library(OSL)is designed to optimize the parameters for video encoding and forward error correction.Adapted to the packet-loss rate and bandwidth in practical UAV wireless network,the proposed OSL can facilitate the encoding of video sequences and the recovery of degraded videos with optimal performance.Experimental results demonstrate that the proposed solution can keep intelligent video analysis working efficiently with adverse UAV wireless links,and is capable of maximizing the inference accuracy of Multi-Object Tracking(MOT)algorithms in various scenarios.

An Intelligent Tool to Support Requirements Analysis and Conceptual Design of Database Design

As an application of artificial intelligence and expert system technology to database design,this paper presents an intelligent design tool NITDT,which comprises a requirements specification lan- guage NITSL,a knowledge representation language NITKL,and an inference engine with uncertainty reasoning capability.NITDT now covers the requirements analysis and conceptual design of database design.However,it is possible to be integrated with another database design tool, NITDBA,developed also at NIT to become an integrated design tool supporting the whole process of database design.

Development of community health service-oriented computer-assisted information system for diagnosis and treatment of respiratory diseases

Objective:Community health services are an emerging trend.We have found in practice that diagnosis and treatment of respiratory diseases in the community are distinct.The respiratory department’s daily work involves a number of outpatient registration items and a vast workload.The routine manual operation is inefficient and it is not convenient to make effective statistical analysis of the outpatient data to identify the risk factors closely related to diseases.Therefore,it is imperative to process the outpatient information of patients with respiratory diseases effectively and efficiently in a unified manner by means of computer technology.Methods:The design and realization of the Community Health Service-oriented computerassisted Information System for Diagnosis and Treatment of Respiratory Diseases(CHS-DTRD)was completed as part of the community intervention study on bronchial asthma that was carried out jointly by the Nanjing First Hospital Affiliated to Nanjing Medical University and the Hospital of Nanjing University of Science&Technology,and based on 2 years of experience and the needs of an overall analysis.Results:The computer-assisted information system for diagnosis and treatment was developed using Java Server Page(JSP)technology and introducing the advanced Asynchronous JavaScript XML(AJAX)technique and MS-SQL Server was used in the background database.CHS-DTRD was composed of eight functional modules(outpatient data maintenance,outpatient appointment,intelligent analysis for disease risk factors,query and statistics,data dictionary maintenance,database manipulation,access control,and system configuration).CHS-DTRD featured a friendly interface,convenient operation,and stability and reliability.Conclusion:Community health-oriented diagnosis and treatment of respiratory diseases is simple,programmable,and intuitive,thus the workload of physicians is significantly reduced and the work efficiency is improved.This system facilitates an intelligent analysis of disease risk factors using data mining technology,and provides physicians with suggestions on intelligent analysis for diagnosis of disease and conclusion of disease causes.

Cow behavior recognition based on image analysis and activities

For the rapid and accurate identification of cow reproduction and healthy behavior from mass surveillance video,in this study,400 head of young cows and lactating cows were taken as the research object and analyzed cow behavior from the dairy activity area and milk hall ramp.The method of object recognition based on image entropy was proposed,aiming at the identification of motional cow object behavior against a complex background.Calculating a minimum bounding box and contour mapping were used for the real-time capture of rutting span behavior and hoof or back characteristics.Then,by combining the continuous image characteristics and movement of cows for 7 d,the method could quickly distinguish abnormal behavior of dairy cows from healthy reproduction,improving the accuracy of the identification of characteristics of dairy cows.Cow behavior recognition based on image analysis and activities was proposed to capture abnormal behavior that has harmful effects on healthy reproduction and to improve the accuracy of cow behavior identification.The experimental results showed that,through target detection,classification and recognition,the recognition rates of hoof disease and heat in the reproduction and health of dairy cows were greater than 80%,and the false negative rates of oestrus and hoof disease were 3.28%and 5.32%,respectively.This method can enhance the real-time monitoring of cows,save time and improve the management efficiency of large-scale farming.