Using Extension Theory and Fuzzy Analytic Hierarchy Process on Heterogeneous Wireless Network Selection Algorithm

In order to solve the problem that determining decision factors weights is of subjectivity in heterogeneous wireless network selection algorithm, a network selection algorithm based on extension theory and fuzzy analytic hierarchy process （FAHP） is proposed in this paper. In addition, user and operator codetermine the optimal network using the proposed algorithm, which can give consideration to user and operator benefits. The fuzzy judgment matrix is coustructed by membership degree of decision factors which is calculated according to extension theory. The comprehensive weight of each decision factor is obtained using FAHP. Finally, the optimal network is selected through total property value ranldng of each candidate network under user preference and operator preference. The simulation results show that the proposed algorithm can select the optimal network efficiently and accurately, satisfy user preference, and implement load balance between networks.

Application of fuzzy analytic hierarchy process and neural network in power transformer risk assessment

In operation,risk arising from power transformer faults is of much uncertainty and complicacy.To timely and objectively control the risks,a transformer risk assessment method based on fuzzy analytic hierarchy process(FAHP) and artificial neural network(ANN) from the perspective of accuracy and quickness is proposed.An analytic hierarchy process model for the transformer risk assessment is built by analysis of the risk factors affecting the transformer risk level and the weight relation of each risk factor in transformer risk calculation is analyzed by application of fuzzy consistency judgment matrix;with utilization of adaptive ability and nonlinear mapping ability of the ANN,the risk factors with large weights are used as input of neutral network,and thus intelligent quantitative assessment of transformer risk is realized.The simulation result shows that the proposed method increases the speed and accuracy of the risk assessment and can provide feasible decision basis for the transformer risk management and maintenance decisions.

Seismic risk evaluation for a planning mountain tunnel using improved analytical hierarchy process based on extension theory

Seismic risk evaluation(SRE) in early stages(e.g., project planning and preliminary design)for a mountain tunnel located in seismic areas has the same importance as that in final stages(e.g.,performance-based design, structural analysis, and optimization). SRE for planning mountain tunnels bridges the gap between the planning on the macro level and the design/analysis on the micro level regarding the risk management of infrastructural systems. A transition from subjective or qualitative description to objective or quantitative quantification of seismic risk is aimed to improve the seismic behavior of the mountain tunnel and thus reduce the associated seismic risk. A new method of systematic SRE for the planning mountain tunnel was presented herein. The method employs extension theory(ET)and an ET-based improved analytical hierarchy process. Additionally, a new risk-classification criterion is proposed to classify and quantify the seismic risk for a planning mountain tunnel. This SRE method is applied to a mountain tunnel in southwest China, using the extension model based on matter element theory and dependent function operation.The reasonability and flexibility of the SRE method for application to the mountain tunnel are illustrated.According to different seismic risk levels and classification criteria, methods and measures for improving the seismic design are proposed, which can reduce the seismic risk and provide a frame of reference for elaborate seismic design.

Concurrent Material Selection of Natural Fibre Filament for Fused Deposition Modeling Using Integration of Analytic Hierarchy Process/Analytic Network Process

The employment of natural fibres in fused deposition modeling has raised much attention from researchers in finding a suitable formulation for the natural fibre composite filaments.Moreover,selection of suitable natural fibres for fused deposition modeling should be performed before the development of the composites.It could not be performed without identifying selection criteria that comprehend both materials and fused deposition modeling process requirements.Therefore,in this study,integration of the Analytic Hierarchy Process(AHP)/Analytic Network Process(ANP)has been introduced in selecting the natural fibres based in different clusters of selection concurrently.The selection process has been performed based on the interdependency among the selection criteria.Pairwise comparison matrices are constructed based on AHP’s hierarchical model and super matrices are constructed based on the ANP’s network model.As a result,flax fibre has ranked at the top of the selection by scored 19.5%from the overall evaluation.Flax fibre has excellent material properties and been found in various natural fibre composite applications.Further investigation is needed to study the compatibility of this fibre to be reinforced with a thermoplastic polymer matrix to develop a resultant natural fibre composite filament for fused deposition modeling.

Risk Assessment of Distributed Energy System Based on Fuzzy Analytic Hierarchy Process

Risk assessment of distributed energy system often has uncertainty and subjective problems. The problems will have some impact on the results. To solve the problems, a method of improved fuzzy analytic hierarchy process is proposed. By using the fuzzy analytic hierarchy process method, a hierarchical analysis model is established. And then according to the given judgment matrix of each index layer, we calculate whether it meets the consistency condition. And then if the judgment matrix does not meet the consistency condition, the problem will be solved by the improving of particle swarm optimization (PSO) with Kalman filter. The practice in the distributed energy system shows that the method can not only fully reflect the fuzziness of assessment elements and process, but also reduce the influence of individual subjective factors and better evaluation results can be achieved.

MULTIPLE ATTRIBUTE NETWORK SELECTION ALGORITHM BASED ON AHP AND SYNERGETIC THEORY FOR HETEROGENEOUS WIRELESS NETWORKS

It is a hot issue in communication research field to select the best network for Heterogeneous Wireless Networks(HWNs),and it is also a difficult problem to reduce the handoff number of vertical handoff.In order to solve this problem,the paper proposes a multiple attribute network selection algorithm based on Analytic Hierarchy Process(AHP)and synergetic theory.The algorithm applies synergetics to network selection,considering the candidate network as a compound system composed of multiple attribute subsystems,and combines the subsystem order degree with AHP weight to obtain entropy of the compound system,which is opposite the synergy degree of a network system.The greater the synergy degree,the better the network performance.The algorithm takes not only the coordination of objective attributes but also Quality of Service(QoS)requirements into consideration,ensuring that users select the network with overall good performance.The simulation results show that the proposed algorithm can effectively reduce the handoff number and provide uses with satisfactory QoS according to different services.

Optimization Model Proposal for Traffic Differentiation in Wireless Sensor Networks

Wireless sensor networks(WSNs)are characterized by heterogeneous traffic types(audio,video,data)and diverse application traffic requirements.This paper introduces three traffic classes following the defined model of heterogeneous traffic differentiation in WSNs.The requirements for each class regarding sensitivity to QoS(Quality of Service)parameters,such as loss,delay,and jitter,are described.These classes encompass real-time and delay-tolerant traffic.Given that QoS evaluation is a multi-criteria decision-making problem,we employed the AHP(Analytical Hierarchy Process)method for multi-criteria optimization.As a result of this approach,we derived weight values for different traffic classes based on key QoS factors and requirements.These weights are assigned to individual traffic classes to determine transmission priority.This study provides a thorough comparative analysis of the proposed model against existing methods,demonstrating its superior performance across various traffic scenarios and its implications for future WSN applications.The results highlight the model’s adaptability and robustness in optimizing network resources under varying conditions,offering insights into practical deployments in real-world scenarios.Additionally,the paper includes an analysis of energy consumption,underscoring the trade-offs between QoS performance and energy efficiency.This study presents the development of a differentiated services model for heterogeneous traffic in wireless sensor networks,considering the appropriate QoS framework supported by experimental analyses.

DECISION MAKING - THE ANALYTIC HIERARCHY AND NETWORK PROCESSES (AHP/ANP)

This is the first part of an introduction to multicriteria decision making using the Analytic Hierarchy Process (AHP) and its generalization, the Analytic Network Process (ANP). The discussion involves individual and group decisions both with the independence of the criteria from the alternatives as in the AHP and also with dependence and feedback in the entire decision structure as in the ANP. This part explains the Analytic Hierarchy Process, with examples, and presents in some detail the mathematical foundations. An exposition of the Analytic Network Process and its applications will appear in later issues of this journal.

Room thermal load prediction based on analytic hierarchy process and back-propagation neural networks

Accurate prediction of the heat load is the basic premise of intelligent regulation of the heating system,which helps to realize effective management of heating,ventilation,air conditioning system.For the problem that the weight of each influencing factor is not taken into account in the current heat load prediction and is not highly targeted,this article deeply explores the influence of different factors on the room heat load,and we propose a method to calculate room heat load prediction based on the combination of analytic hierarchy process(AHP)and back-propagation(BP)neural network.Firstly,eight environmental factors affecting the heat load are selected as prediction inputs through parametric analysis,and then the weights of each input are determined by AHP and normalize the prediction data by combining expert opinions,and finally do one-to-one training the quantified score and the room heat load to predict the future heat load by BP neural network.The simulation tests show that the mean absolute relative error(MARE)of the proposed prediction method is 5.40%.This article also verifies the influence of different expert opinions on the stability of the model.The results show that the proposed method can guarantee higher prediction accuracy and stability.

未来社区健康场景服务质量评价指标体系构建研究

背景在国家推动“以治病为中心”向“以健康为中心”理念转变的背景下,浙江省率先打造面向全人群和全生命周期的未来社区健康场景,为基层卫生健康综合改革提供了“浙江样板”,构建一套科学有效的未来社区健康场景服务质量评价指标体系具有重要的理论意义和实践价值。目的构建浙江省未来社区健康场景服务质量评价指标体系,为提升社区健康服务能力和质量,推动人群健康目标实现提供参考。方法基于SERVQUAL理论模型,通过政策分析、文献研究和实地调研建立初始指标池;2023年10—12月,采用两轮德尔菲专家咨询法确定指标体系,并运用层次分析法确定各指标的权重和组合权重。结果两轮专家咨询均有17位专家参与,其中高级职称共12名(70.6%);工作年限≥10年15名(88.2%);未来社区的管理人员和医务人员共5名(29.4%)。两轮咨询专家积极性均为1.0,权威系数分别为0.862和0.842,协调程度逐轮提高,最终构建的指标体系包含5个一级指标、13个二级指标、36个三级指标。一级指标中,有形性、可靠性、保证性、响应性、移情性的权重分别为0.168、0.180、0.240、0.178、0.232;二级指标中,场地设施、数字化设备、服务提供、健康监测、服务效率、服务可及性、危机预防和应急救援能力、专业技能、活动组织、智能平台维护、服务态度和情感支持、服务效果、个性化服务的权重分别为0.399、0.601、0.672、0.328、0.487、0.171、0.342、0.410、0.416、0.174、0.284、0.323、0.393。结论本研究构建的浙江省未来社区健康场景服务质量评价指标体系科学可靠,具有较强的系统性、创新性、可操作性和应用价值,是开展未来社区健康场景评价的有效工具,希望能够为政府制定改进策略和相关政策提供参考。

A RISK ASSESSMENT METHOD OF THE WIRELESS NETWORK SECURITY

The core of network security is the risk assessment. In this letter,a risk assessment method is introduced to estimate the wireless network security. The method,which combines Analytic Hier-archy Process (AHP) method and fuzzy logical method,is applied to the risk assessment. Fuzzy logical method is applied to judge the important degree of each factor in the aspects of the probability,the influence and the uncontrollability,not to directly judge the important degree itself. The risk as-sessment is carved up 3 layers applying AHP method,the sort weight of the third layer is calculated by fuzzy logical method. Finally,the important degree is calculated by AHP method. By comparing the important degree of each factor,the risk which can be controlled by taking measures is known. The study of the case shows that the method can be easily used to the risk assessment of the wireless network security and its results conform to the actual situation.

Fuzzy analytic network process(FANP)approach in formulating infrastructural decisions of sustainable manufacturing strategy

This paper explores a fuzzy analytic network process(FANP)approach in identifying the content of manufacturing strategy infrastructural decisions that integrates sustainability and classical manufacturing strategy framework with firm size component.The findings are as follows:(1)firms must ensure highquality product requirements with a make-to-order production system;(2)large firms must prioritize decentralization of functional areas but they must also provide higher systems integration of all production-related information to mobilize better communication channels;(3)large firms must employ highly skilled human resources in order to provide strong support on functional areas;and(4)small and medium enterprises must focus on product introduction to the market as a strategy priority area.The main contribution of this paper is the decision-making framework under uncertainty that holistically identifies the decisions that comprise a sustainable manufacturing strategy which may serve as guidelines in improving existing sustainable manufacturing practices or in creating new ones.

Multifunctional Landscape Actor-Network Construction from the Perspective of Rural Tourism Experiences

During the construction of multifunctional landscape(MFL) actor-network, economic, social, and ecological functions presented significant differences, which resulted from the different roles and effects of various heterogeneous actors according to the tourism experience. In Hekou Village at the border area between China and North Korea, the roles and effects of heterogeneous actors during the MFL actor-network construction were analyzed by means of the analytic network process(ANP), which verified the Groundings-Entrepreneurship-Markets(GEM) theoretical framework of the MFL actor-network that assumed tourism experiences were core actors, and economic, social, and ecological landscape actors acted as support. Research results showed that in the MFL actornetwork construction, social and economic functions of landscapes were strong, while ecological and tourism experience functions were weak and that folk customs and land utilization were key actors of the MFL actor-network construction. In the MFL actor-network construction, actors played different roles and had different effects on the network. Intelligence facilities and rurality were critical to drive the MFL actor network translation process and pass through "obligatory passage point". By changing the interaction mode and intensity of the actors, the MFL actor-network could be promoted.

Evaluation Model of Emergency Evacuation Capacity of Subway Station Based on Grounded Theory

In order to evaluate the emergency evacuation capacity of subway stations, the data collected were analyzed based on grounded theory, and an evaluation model of emergency evacuation capacity was constructed by combining the analytic hierarchy process (AHP). Finally, 12 secondary indicators (categories) and 4 primary indicators (main categories) were obtained, among which the primary indicators were management factors, emergency response, construction factors and personnel factors. From the weight value calculated by analytic hierarchy process, we can see that management factors and emergency response have great influence on the emergency evacuation capacity of subway stations. Therefore, we should focus on management factors and emergency response to improve the emergency evacuation capacity of subway stations.

A Novel Features Prioritization Mechanism for Controllers in Software-Defined Networking

The controller in software-defined networking(SDN)acts as strategic point of control for the underlying network.Multiple controllers are available,and every single controller retains a number of features such as the OpenFlow version,clustering,modularity,platform,and partnership support,etc.They are regarded as vital when making a selection among a set of controllers.As such,the selection of the controller becomes a multi-criteria decision making(MCDM)problem with several features.Hence,an increase in this number will increase the computational complexity of the controller selection process.Previously,the selection of controllers based on features has been studied by the researchers.However,the prioritization of features has gotten less attention.Moreover,several features increase the computational complexity of the selection process.In this paper,we propose a mathematical modeling for feature prioritization with analytical network process(ANP)bridge model for SDN controllers.The results indicate that a prioritized features model lead to a reduction in the computational complexity of the selection of SDN controller.In addition,our model generates prioritized features for SDN controllers.

Mathematical Modeling in Social Network Analysis： Using TOPSIS to Find Node Influences in a Social Network

In a social network analysis the output provided includes many measures and metrics. For each of these measures and metric, the output provides the ability to obtain a rank ordering of the nodes in terms of these measures. We might use this information in decision making concerning disrupting or deceiving a given network. All is fine when all the measures indicate the same node as the key or influential node. What happens when the measures indicate different key nodes？ Our goal in this paper is to explore two methodologies to identify the key players or nodes in a given network. We apply TOPSIS to analyze these outputs to find the most influential nodes as a function of the decision makers＇ inputs as a process to consider both subjective and objectives inputs through pairwise comparison matrices. We illustrate our results using two common networks from the literature： the Kite network and the Information flow network from Knoke and Wood. We discuss some basic sensitivity analysis can may be applied to the methods. We find the use of TOPSIS as a flexible method to weight the criterion based upon the decision makers＇ inputs or the topology of the network.

Using Mathematical Models in Decision Making Methodologies to Find Key Nodes in the Noordin Dark Network

A Dark Network is a network that cannot be accessed through tradition means. Once uncovered, to any degree, dark network analysis can be accomplished using the SNA software. The output of SNA software includes many measures and metrics. For each of these measures and metric, the output in ORA additionally provides the ability to obtain a rank ordering of the nodes in terms of these measures. We might use this information in decision making concerning best methods to disrupt or deceive a given dark network. In the Noordin Dark network, different nodes were identified as key nodes based upon the metric used. Our goal in this paper is to use methodologies to identify the key players or nodes in a Dark Network in a similar manner as we previously proposed in social networks. We apply two multi-attribute decision making methods, a hybrid AHP & TOPSIS and an average weighted ranks scheme, to analyze these outputs to find the most influential nodes as a function of the decision makers’ inputs. We compare these methods by illustration using the Noordin Dark Network with seventy-nine nodes. We discuss sensitivity analysis that is applied to the criteria weights in order to measure the change in the ranking of the nodes.

Establishment of an indicator framework for global One Health Intrinsic Drivers index based on the grounded theory and fuzzy analytical hierarchy-entropy weight method

Background:One Health has become a global consensus to deal with complex health problems.However,the pro‑gress of One Health implementation in many countries is still relatively slow,and there is a lack of systematic evalua‑tion index.The purpose of this study was to establish an indicator framework for global One Health Intrinsic Drivers index(GOH-IDI)to evaluate human,animal and environmental health development process globally.Method:First,82 studies were deeply analyzed by a grounded theory(GT)method,including open coding,axial coding,and selective coding,to establish a three-level indicator framework,which was composed of three selective codes,19 axial codes,and 79 open codes.Then,through semi-structured interviews with 28 health-related experts,the indicators were further integrated and simplifed according to the inclusion criteria of the indicators.Finally,the fuzzy analytical hierarchy process combined with the entropy weight method was used to assign weights to the indi‑cators,thus,forming the evaluation indicator framework of human,animal and environmental health development process.Results:An indicator framework for GOH-IDI was formed consisting of three selective codes,15 axial codes and 61 open codes.There were six axial codes for“Human Health”,of which“Infectious Diseases”had the highest weight(19.76%)and“Injuries and Violence”had the lowest weight(11.72%).There were four axial codes for“Animal Health”,of which“Animal Epidemic Disease”had the highest weight(39.28%)and“Animal Nutritional Status”had the low‑est weight(11.59%).Five axial codes were set under“Environmental Health”,among which,“Air Quality and Climate Change”had the highest weight(22.63%)and“Hazardous Chemicals”had the lowest weight(17.82%).Conclusions:An indicator framework for GOH-IDI was established in this study.The framework were universal,balanced,and scientifc,which hopefully to be a tool for evaluation of the joint development of human,animal and environmental health in diferent regions globally.

Application of FAHP and Artificial Neural Network on Clothing Plant Location

Clothing manufacturers＇ direct investment and joint ventures in developing regions have seen to grow rapidly in the past few decades. Non-optimized selection can contribute to adverse effects affecting the performance of the plants on aspects of productivity, manufacturing and logistics cost. Selection of proper plant location is thus crucial. The conventional approaches to sites location are based on the factors and their weights. However, determining the weight of each factor is very difficult and time consuming. While the situation is changed, all the work must be redone again. This study aims to develop a decision-making system on clothing plant location for Hoog Kong clothing manufacturer. The proposed system utilizes artificial neural network to study the relationship between the factors and the suitability index of candidate sites. Firstly, the factors are stratified using the fuzzy analytical hierarchy process （FAHP） by review the related references and interviewing the experts. Secondly, the corresponding data are collected from the experts by questionnaire and the related government publication. Finally, the feedforward neural network with error backpropagation（EBP） learning algorithm is trained and applied to make decision. The results show that the proposed system performs well and has the characteristic of adaptability and plasticity.