Improving Land Resource Evaluation Using Fuzzy Neural Network Ensembles

Land evaluation factors often contain continuous-, discrete- and nominal-valued attributes. In traditional land evaluation, these different attributes are usually graded into categorical indexes by land resource experts, and the evaluation results rely heavily on experts＇ experiences. In order to overcome the shortcoming, we presented a fuzzy neural network ensemble method that did not require grading the evaluation factors into categorical indexes and could evaluate land resources by using the three kinds of attribute values directly. A fuzzy back propagation neural network （BPNN）, a fuzzy radial basis function neural network （RBFNN）, a fuzzy BPNN ensemble, and a fuzzy RBFNN ensemble were used to evaluate the land resources in Guangdong Province. The evaluation results by using the fuzzy BPNN ensemble and the fuzzy RBFNN ensemble were much better than those by using the single fuzzy BPNN and the single fuzzy RBFNN, and the error rate of the single fuzzy RBFNN or fuzzy RBFNN ensemble was lower than that of the single fuzzy BPNN or fuzzy BPNN ensemble, respectively. By using the fuzzy neural network ensembles, the validity of land resource evaluation was improved and reliance on land evaluators＇ experiences was considerably reduced.

Application of Bayesian Network Learning Methods to Land Resource Evaluation

Bayesian network has a powerful ability/or reasoning and semantic representation, which combined with qualitative analysis and quantitative analysis, with prior knowledge and observed data, and provides an effective way to deal with prediction, classification and clustering. Firstly, this paper presented an overview of Bayesian network and its characteristics, and discussed how to learn a Bayesian net- work structure from given data, and then constructed a Bayesian network model for land resource evaluation with expert knowledge and the dataset. The experimental results based on the test dataset are that evaluation accuracy is 87.5%, and Kappa index is 0. 826. All these prove the method is feasible and efficient, and indicate that Bayesian network is a promising approach for land resource evaluation.

Research on Tourism Resources Development Pattern Effect Evaluation based on Regression Analysis and Neural Network

In this paper, we conduct research on the tourism resources development pattern effect evaluation based on regression analysis andneural network. Tourism resources development and the protection of all sorts of the contradictions, in the fi nal analysis is the confl ict betweenthe interests of stakeholders. Real life in China, and tourism resources development and protection of the interests of the relevant party basicallyhas the following six parties the local government, investment and the business practice, the original residents, tourists, tourism practitioners, thesocial organization. The survival and the development of general tourism industry is based on the premise of environmental protection, tourismlandscape are carefully protected, let the natural landscape and human landscape form a virtuous cycle, to attract more tourists, promote thesustainable development of scenic spots. Under this basis, this paper proposes the new idea on the issues that is meaningful.

User satisfaction-based quality evaluation model and survey analysis of network information service

On the basis of user satisfaction,authors made research hypotheses by learning from relevant e-service quality evaluation models.A questionnaire survey was then conducted on some content-based websites in terms of their convenience,information quality,personalization and site aesthetics,which may affect the overall satisfaction of users.Statistical analysis was also made to build a user satisfaction-based quality evaluation system of network information service.

Research on Evaluation and Management of Networked Manufacturing Resources Based on WUXIASP

The data models and description of manufacturing resources are discussed for realizing distributed networked manufacturing and the multi-goal evaluating model is put forward. The factors and process in networked manufacturing resources evaluating are given, and the service function and the system architecture of WUXIASP is set up. It is useful to actualize area networked manufacture.

The Application of Fuzzy Evaluation based on GIS in Tianjin Urban Underground Space Resource Appraisal

The exploitation and utilization of the city underground space resource is the important approach of building tri-dimensional and ecological cities, solving the environment,resource,and population crisis and continuing cities development.This article, based on the introduction in detail the overview of regional geology,hydrogeologic condition,engineering geology,environmental geology,etc.in center city of Tianjin,establishes evaluating model of urban underground space resource based on GIS

Information Freshness-Oriented Trajectory Planning and Resource Allocation for UAV-Assisted Vehicular Networks

In this paper,multi-UAV trajectory planning and resource allocation are jointly investigated to improve the information freshness for vehicular networks,where the vehicles collect time-critical traffic information by on-board sensors and upload to the UAVs through their allocated spectrum resource.We adopt the expected sum age of information(ESAoI)to measure the network-wide information freshness.ESAoI is jointly affected by both the UAVs trajectory and the resource allocation,which are coupled with each other and make the analysis of ESAoI challenging.To tackle this challenge,we introduce a joint trajectory planning and resource allocation procedure,where the UAVs firstly fly to their destinations and then hover to allocate resource blocks(RBs)during a time-slot.Based on this procedure,we formulate a trajectory planning and resource allocation problem for ESAoI minimization.To solve the mixed integer nonlinear programming(MINLP)problem with hybrid decision variables,we propose a TD3 trajectory planning and Round-robin resource allocation(TTPRRA).Specifically,we exploit the exploration and learning ability of the twin delayed deep deterministic policy gradient algorithm(TD3)for UAVs trajectory planning,and utilize Round Robin rule for the optimal resource allocation.With TTP-RRA,the UAVs obtain their flight velocities by sensing the locations and the age of information(AoI)of the vehicles,then allocate the RBs to the vehicles in a descending order of AoI until the remaining RBs are not sufficient to support another successful uploading.Simulation results demonstrate that TTP-RRA outperforms the baseline approaches in terms of ESAoI and average AoI(AAoI).

What to Cache：Differentiated Caching Resource Allocation and Management in Information-Centric Networking

Information-centric networking(ICN) aims to improve the efficiency of content delivery and reduce the redundancy of data transmission by caching contents in network nodes. An important issue is to design caching methods with better cache hit rate and achieve allocating on-demand. Therefore, an in-network caching scheduling scheme for ICN was designed, distinguishing different kinds of contents and dynamically allocating the cache size on-demand. First discussing what was appropriated to be cached in nodes, and then a classification about the contents could be cached was proposed. Furthermore, we used AHP to weight different contents classes through analyzing users' behavior. And a distributed control process was built, to achieve differentiated caching resource allocation and management. The designed scheme not only avoids the waste of caching resource, but also further enhances the cache availability. Finally, the simulation results are illustrated to show that our method has the superior performance in the aspects of server hit rate and convergence.

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.

Robustness evaluation method for unmanned aerial vehicle swarms based on complex network theory

Unmanned Aerial Vehicle(UAV)swarms have been foreseen to play an important role in military applications in the future,wherein they will be frequently subjected to different disturbances and destructions such as attacks and equipment faults.Therefore,a sophisticated robustness evaluation mechanism is of considerable importance for the reliable functioning of the UAV swarms.However,their complex characteristics and irregular dynamic evolution make them extremely challenging and uncertain to evaluate the robustness of such a system.In this paper,a complex network theory-based robustness evaluation method for a UAV swarming system is proposed.This method takes into account the dynamic evolution of UAV swarms,including dynamic reconfiguration and information correlation.The paper analyzes and models the aforementioned dynamic evolution and establishes a comprehensive robustness metric and two evaluation strategies.The robustness evaluation method and algorithms considering dynamic reconfiguration and information correlation are developed.Finally,the validity of the proposed method is verified by conducting a case study analysis.The results can further provide some guidance and reference for the robust design,mission planning and decision-making of UAV swarms.

Information resources reorganization and sharing platform of national scientific＆technical document service in China

Reorganization of network information resources for scientific and technical （scitech for abbreviation） documents and development of information infrastructure have brought a great change in China＇s scitech documentation information sharing. It integrated not only information resources, but also systems, technologies and funds. High quality services and effective resources sharing are the main goals of the platform construction. The paper describes briefly the principles and aims of the integration of the scitech information resources and networks. The services of the sharing platforms have been also introduced.

Cluster based hierarchical resource searching model in P2P network

For the problem of large network load generated by the Gnutella resource-searching model in Peer to Peer （P2P） network, a improved model to decrease the network expense is proposed, which establishes a duster in P2P network, auto-organizes logical layers, and applies a hybrid mechanism of directional searching and flooding. The performance analysis and simulation results show that the proposed hierarchical searching model has availably reduced the generated message load and that its searching-response time performance is as fairly good as that of the Gnutella model.

Robust resource allocation for NOMA-assisted heterogeneous networks

As a promising technology to improve spectrum efficiency and transmission coverage,Heterogeneous Network(HetNet)has attracted the attention of many scholars in recent years.Additionally,with the introduction of the Non-Orthogonal Multiple Access(NOMA)technology,the NOMA-assisted HetNet cannot only improve the system capacity but also allow more users to utilize the same frequency band resource,which makes the NOMA-assisted HetNet a hot topic.However,traditional resource allocation schemes assume that base stations can exactly estimate direct link gains and cross-tier link gains,which is impractical for practical HetNets due to the impact of channel delays and random perturbation.To further improve energy utilization and system robustness,in this paper,we investigate a robust resource allocation problem to maximize the total Energy Efficiency(EE)of Small-Cell Users(SCUs)in NOMA-assisted HetNets under imperfect channel state information.By considering bounded channel uncertainties,the robust resource optimization problem is formulated as a mixed-integer and nonlinear programming problem under the constraints of the cross-tier interference power of macrocell users,the maximum transmit power of small base station,the Resource Block(RB)assignment,and the quality of service requirement of each SCU.The original problem is converted into an equivalent convex optimization problem by using Dinkelbach's method and the successive convex approximation method.A robust Dinkelbach-based iteration algorithm is designed by jointly optimizing the transmit power and the RB allocation.Simulation results verify that the proposed algorithm has better EE and robustness than the existing algorithms.

An Analysis of the Value of Additional Information Provided by Water Quality Measurement Network

European Community policy concerning water is placing increasing demands on the acquisition of information about the quality of aquatic environments. The cost of this information has led to a reflection on the rationalization of monitoring networks and, therefore, on the economic value of information produced by these networks. The aim of this article is to contribute to this reflection. To do so, we used the Bayesian framework to define the value of additional information in relation to the following three parameters: initial assumptions (prior probabilities) on the states of nature, costs linked to a poor decision (error costs) and accuracy of additional information. We then analyzed the impact of these parameters on this value, particularly the combined role of prior probabilities and error costs that increased or decreased the value of information depending on the initial uncertainty level. We then illustrated the results using a case study of a stream in the Bas-Rhin department in France.

Developing a Comprehensive Regime for Personal Information Protection in Networked Chinese Public Sectors

With the increasing sharing and reuse of personal information resources for better public services, the effective protection and management of personal information as organizational and individual assets as well as social resources are becoming more and more important in networked Chinese public sectors. Existing studies of personal information protection in China is mainly conducted from the legal perspective with a focus on the development of appropriate legislation and policies at the national level. There is little research on how specific legislation and polices can actually be implemented in an effective manner and what impacts such legislation and policies have on individuals, organizations, and the society. To adequately address this issue, this study investigates the legal requirements for personal information protection based on the relevant laws, regulations, and standards in China. It proposes a comprehensive regime for personal information protection in the networked public sectors in China. Such a regime takes the advantages of existing discipline-based approaches, legal requirements, and control mechanisms for personal information protection. It can be used to facilitate the provision of public services in the networked Chinese public sectors through the adequate protection of personal information and the effective management of personal information.

A review and an outlook of the National Cultural Information Resources Sharing Project

This paper discusses the Project's organization system, technical system, creation of digital resources and service mode. It also summarizes achievements gained since the commencement of the Project, and also analyzes some of the more important issues during implementation stage and gives a few suggestions of the future development during the next stage of the 11thFive-Year Plan.

中国稀土政策演进分析及评价研究

稀土是国家发展与产业升级的重要资源,建立完善的稀土政策体系至关重要。通过构建稀土政策分析框架,利用文本挖掘、社会网络、PMC指数模型方法,从稀土政策演进历程、政策关系网络和政策量化评价三个方面,对我国1985年至今发布的48项稀土政策进行分析。结果表明,我国稀土政策演进分为4个阶段,其中规范稀土资源开采程序、整顿稀土市场秩序一直是我国稀土政策的核心;政策网络体系已初步构建,但政策间关联性较差,存在较多孤立政策,政策协同关系需要加强;政策总体设计较为合理,但在激励措施以及效力级别等方面略有不足。最后,针对我国稀土政策的特点及存在的不足提出了优化与完善建议。

粤港澳大湾区内地城市群路网韧性的贝叶斯网络评估

随着我国城市化进程的推进,城市路网的韧性问题愈发凸显。构建了一种基于贝叶斯网络模型的城市路网韧性评价模型,并以粤港澳大湾区内地城市群为例,评估了2000—2019年该地区9个城市的路网韧性。基于韧性功能函数从容灾性、稳定性、重构性、恢复性4个方面建立功能层,选取稳定性、可变性、可维护性、可靠性、服务性、安全性、鲁棒性、可修性、适应性9个因素建立性能层,选取客运量、公共汽车数量、道路面积率、出租车数量、交通事故死亡人数、公共交通投资、每万人公共汽车数、道路运输从业人数、人均道路面积9个因素建立因素层。研究结果表明:路网韧性指数最高的为深圳(60%),而最低的为中山(43%);广州、深圳、珠海、东莞的路网韧性一直稳定增长,其余城市的路网韧性浮动较小;路网韧性并非总是随着城市GDP的增长而提高,还与人均GDP有关;敏感性分析表明,路网重构性、路网可靠性、交通事故死亡人数分别为各自所在层中对路网韧性影响最大的因素;加强中心城市与其他城市之间的联系可以提高城市路网韧性。研究成果可为粤港澳大湾区城市群交通路网功能完善与韧性提升提供技术参考。

政府旅游数据开放的评价指标体系构建与组态分析:基于21个省级行政区的数据

在信息时代和智慧旅游背景下,政府主动对外开放内部的旅游数据,有利于充分释放旅游数据资源的商业价值与社会价值。使用变异系数法与熵权法进行组合赋权,构建了政府旅游数据开放评价指标体系,计算21个省级行政区的具体得分,并采用模糊集定性比较方法进行高评价值与低评价值条件组态分析。结果表明:指标体系包含4项一级指标、17项二级指标与51项三级指标,可以对当前省级行政区的旅游数据开放绩效进行有效评价;利用层、数据层是权重较高的一级指标,法律政策效率与内容、平台关系等是权重较高的二级指标;高评价值组态为综合发展型、数据辅助应用型,低评价值组态为政策与利用短板型、平台与数据问题型。研究结果可以为旅游数据开放评价相关学术研究与管理实践提供参考。