基于改进Fuzzy ART的自适应雷达信号分选

侦察接收机对获取的辐射源波形去交织以分离不同信号,称为信号分选,是电磁频谱战系统的核心技术.复杂电磁环境下脉冲流密度大、时域波形及诸域特征严重交叠,导致多数基于无监督模型的信号分选方法难以胜任.提出一种可自适应调整警戒阈值的模糊自适应共振理论(AVT fuzzy ART)聚类算法,基于对属性差异敏感的曼哈顿距离自适应调整警戒阈值,依据在线累积数据得出的辐射源瞬态聚类概率对警戒阈值动态加权.仿真结果表明,该方法能在无历史先验信息的条件下胜任多类别辐射源信号去交错.

基于Fuzzy Matter-Element模型的电力上市公司财务核心竞争能力评价

鉴于电力上市公司财务核心竞争能力评价的复杂性以及单项指标评价结果的不相容性,本文在模糊物元分析的基础上,将熵权的理论方法与海明贴近度的概念相结合,建立了电力上市公司财务核心竞争能力评价的模糊物元模型。把不同电力企业作为物元的事物,以它们的各项评价指标及相应的模糊量值构造模糊物元,通过计算与理想模糊物元之间的海明贴近度,实现对上市电力公司财务核心竞争能力的综合评价。

Evaluation model of venture investment based on fuzzy matter-element method of combined weight

An evaluation model of an international venture investment project on the basis of fuzzy matter-element and combined weight methods is introduced. First, the compound fuzzy matter-element of optimal subordinate degree is constructed on the principle of the bigger-more-optimal or the less-more-optimal depending on the actual evaluation indicators, and combined with standard fuzzy matter-element to form a difference-square fuzzy matter-element. Secondly, a combined weight is calculated by both information entropy and the expert grading method. Finally, the compound fuzzy matter-element of Euclidian approach degree by M(·,+)method is constituted and used to classify venture investment projects. Based on the model above, six venture investment projects in a company are evaluated, and the results show that the projects are all good, which is demonstrated by the good income of the projects. Therefore, the coincidence of evaluation results and actual operation status indicates that the model is of great value in practical application.

Attribute Reduction of Hybrid Decision Information Systems Based on Fuzzy Conditional Information Entropy

The presence of numerous uncertainties in hybrid decision information systems(HDISs)renders attribute reduction a formidable task.Currently available attribute reduction algorithms,including those based on Pawlak attribute importance,Skowron discernibility matrix,and information entropy,struggle to effectively manages multiple uncertainties simultaneously in HDISs like the precise measurement of disparities between nominal attribute values,and attributes with fuzzy boundaries and abnormal values.In order to address the aforementioned issues,this paper delves into the study of attribute reduction withinHDISs.First of all,a novel metric based on the decision attribute is introduced to solve the problem of accurately measuring the differences between nominal attribute values.The newly introduced distance metric has been christened the supervised distance that can effectively quantify the differences between the nominal attribute values.Then,based on the newly developed metric,a novel fuzzy relationship is defined from the perspective of“feedback on parity of attribute values to attribute sets”.This new fuzzy relationship serves as a valuable tool in addressing the challenges posed by abnormal attribute values.Furthermore,leveraging the newly introduced fuzzy relationship,the fuzzy conditional information entropy is defined as a solution to the challenges posed by fuzzy attributes.It effectively quantifies the uncertainty associated with fuzzy attribute values,thereby providing a robust framework for handling fuzzy information in hybrid information systems.Finally,an algorithm for attribute reduction utilizing the fuzzy conditional information entropy is presented.The experimental results on 12 datasets show that the average reduction rate of our algorithm reaches 84.04%,and the classification accuracy is improved by 3.91%compared to the original dataset,and by an average of 11.25%compared to the other 9 state-of-the-art reduction algorithms.The comprehensive analysis of these research results clearly indicates that our algorithm is highly effective in managing the intricate uncertainties inherent in hybrid data.

New Configurations of the Fuzzy Fractional Differential Boussinesq Model with Application in Ocean Engineering and Their Analysis in Statistical Theory

The fractional-order Boussinesq equations(FBSQe)are investigated in this work to see if they can effectively improve the situation where the shallow water equation cannot directly handle the dispersion wave.The fuzzy forms of analytical FBSQe solutions are first derived using the Adomian decomposition method.It also occurs on the sea floor as opposed to at the functionality.A set of dynamical partial differential equations(PDEs)in this article exemplify an unconfined aquifer flow implication.Thismethodology can accurately simulate climatological intrinsic waves,so the ripples are spread across a large demographic zone.The Aboodh transform merged with the mechanism of Adomian decomposition is implemented to obtain the fuzzified FBSQe in R,R^(n) and(2nth)-order involving generalized Hukuhara differentiability.According to the system parameter,we classify the qualitative features of the Aboodh transform in the fuzzified Caputo and Atangana-Baleanu-Caputo fractional derivative formulations,which are addressed in detail.The illustrations depict a comparison analysis between the both fractional operators under gH-differentiability,as well as the appropriate attributes for the fractional-order and unpredictability factorsσ∈[0,1].A statistical experiment is conducted between the findings of both fractional derivatives to prevent changing the hypothesis after the results are known.Based on the suggested analyses,hydrodynamic technicians,as irrigation or aquifer quality experts,may be capable of obtaining an appropriate storage intensity amount,including an unpredictability threshold.

基于Fuzzy-DEMATEL的埃塞俄比亚纺织服装业可持续发展关键影响因素分析

为探讨埃塞俄比亚纺织服装业可持续发展影响因素之间的作用关系并确定关键影响因素,本文结合文献研究和10位投资或服务于埃塞俄比亚纺织服装业的资深专家半结构化访谈的数据,借助扎根理论的研究方法,总结并归纳埃塞俄比亚纺织服装业可持续发展的影响因素;采用Fuzzy-DEMATEL法,分析该领域内12位专家和学者(不包含10位受访者)对各因素之间相互影响程度的评价,定量识别埃塞俄比亚纺织服装业可持续发展的关键影响因素。研究结果表明:埃塞俄比亚纺织服装业的可持续发展在企业、产业、政府三个维度上受到15个影响因素的制约,其中劳动生产率、基础设施建设、内生动力、政策和制度支持及政府自身建设为五项关键影响因素。相应地,该产业的可持续关键发展策略是优化生产管理、提升员工技能、加大投资关键基础建设、促进技术创新和知识转移、建立健全政策和监管机制、提升政府官员的专业能力和服务水平。通过Fuzzy-DEMATEL方法系统解析了影响因素对埃塞俄比亚纺织服装业可持续发展的复杂作用关系,为促进该国纺织服装业的进一步发展指明了方向。

River Health Assessment Based on Fuzzy Matter-element Model

[Objective] The study aimed to assess the health state of rivers by using fuzzy matter-element model.[Method] Based on fuzzy matter-element analysis theory,the assessment model of river health was established,then a modified method to calculate the superior subordinate degree was put forward according to Hamming distance.Afterwards,a multi-level evaluation model,which contained the assessment indicators about hydrological features,ecological characteristics,environmental traits and service function,was set up based on this method above.Finally,the model was applied in the health assessment of Qinhuai River.[Result] The health state of Qinhuai River was at medium level.This assessment result was consistent with that of comprehensive index method,and it showed that the multi-level fuzzy matter-element model was effective in the assessment of river health.[Conclusion] The research provided an effective method to evaluate the state of river health.

Optimizing selection of bridge raft based on fuzzy matter-element model and combination weighting

It＇ s a necessary selection to support the maneuver across Yangtze River by floating bridge constructed by portable steel bridge and civilian ships. It is a comprehensive index for the scheme of bridge raft, containing a variety of technical factors and uncertainties. The optimization is the selection in the constructing time, quantity of equipments and man power. Based on the calculation result of bridge rafts, an evaluating system is established, consisting of index of spacing between interior bays, raft length, truss numbers, operation difficulty and maximal bending stress. A fuzzy matter element model of optimizing selection of bridge rafts was built up by combining quantitative analysis with qualitative analysis. The method of combination weighting was used to calculate the value of weights index to reduce the subjective randomness. The sequence of schemes and the optimization resuh were gained finally based on euclid approach degree. The application result shows that it is simple and practical.

Research on Maintainability Evaluation Model Based on Fuzzy Theory

Maintainability influencing attributes are analyzed, their weight and value calculating methods are given, and the maintainability fuzzy evaluation method is proposed based on the relative closeness. According to the maintenance task simulation operated in virtual environment, the maintainability virtual evaluation model is built by analyzing the maintenance task for each replaceable unit of product. At last, a case study is given based upon the main landing gear system of a certain type civil aircraft, and the result indicates that the model is suitable for maintainability qualitative evaluation and can support maintainability concurrent design.

ESTIMATION METHOD FOR AIRCRAFT SIMILARITY BASED ON FUZZY THEORY AND GREY INCIDENCE ANALYSIS

An estimation method for aircraft similarity based on fuzzy theory and grey incidence analysis is presented. This estimation method is made up of the triangular fuzzy transforming model of linguistic variables and the method of grey incidence analysis. Nine feature attributes of aircraft are selected to estimate the similarity between the new aircraft and the existing aircraft. A new aircraft X and other six existing aircrafts are taken as examples. Analyses show that similarity estimation results obtained from the method are in accordance with practice.

基于IAHP-FUZZY的装配式建筑施工质量风险评价

在国内建筑业升级发展的背景下,具有较多优点的装配式建筑得到了全面发展。为完善装配式建筑施工过程质量风险评估方式,通过分析研究装配式建筑施工的特点,将装配式建筑施工质量风险评价分为3个阶段:施工准备阶段、施工阶段和施工竣工验收阶段。通过建立一套施工质量风险评价指标体系,采用区间层次分析法确定各指标的对应权重,在该基础上结合隶属度函数和模糊综合评价理论构建装配式建筑施工质量风险评价模型,并将该模型运用到实际工程案例中并验证其可行性。

Fuzzy mathematics and game theory based D2D multicast network construction

Device to device(D2 D) multi-hop communication in multicast networks solves the contradiction between high speed requirements and limited bandwidth in regional data sharing communication services. However, most networking models demand a large control overhead in eNodeB. Moreover, the topology should be calculated again due to the mobility of terminals, which causes the long delay. In this work, we model multicast network construction in D2 D communication through a fuzzy mathematics and game theory based algorithm. In resource allocation, we assume that user equipment(UE) can detect the available frequency and the fuzzy mathematics is introduced to describe an uncertain relationship between the resource and UE distributedly, which diminishes the time delay. For forming structure, a distributed myopic best response dynamics formation algorithm derived from a novel concept from the coalitional game theory is proposed, in which every UE can self-organize into stable structure without the control from eNodeB to improve its utilities in terms of rate and bit error rate(BER) while accounting for a link maintenance cost, and adapt this topology to environmental changes such as mobility while converging to a Nash equilibrium fast. Simulation results show that the proposed architecture converges to a tree network quickly and presents significant gains in terms of average rate utility reaching up to 50% compared to the star topology where all of the UE is directly connected to eNodeB.

Landslides susceptibility mapping in Guizhou province based on fuzzy theory

The purpose of this study was to assess the susceptibility of landslides around the area of Guizhou province based on fuzzy theory.In first instance, slope, elevation, lithology, proximity to tectonic lines, proximity to drainage and annual precipitation were taken as independent, causal factors in this study.A landslide hazard evaluation factor system was established by classifying these factors into more subclasses according to some rules.Secondly, a trapezoidal fuzzy number weighting(TFNW) approach was used to assess the importance of six causal factors to landslides in an ArcGIS environment.Thirdly, a landslide susceptibility map was created based on a weighted linear combination model.According to this susceptibility map, the study area was classified into four categories of landslide susceptibility:low, moderate, high and very high.Finally, in order to verify the results obtained, the susceptibility map and the landslide inventory map were combined in the GIS.In addition, the weighting procedure showed that TFNW is an efficient method for weighting causal landslide factors.

GA-BP Air Quality Evaluation Method Based on Fuzzy Theory

With the rapid development of China’s economy,the scale of the city has been continuously expanding,industrial enterprises have been increasing,the discharge of multiple pollutants has reached the top of the world,and the environmental problems become more and more serious.The air pollution problem is particularly prominent.Air quality has become a daily concern for people.In order to control air pollution,it is necessary to grasp the air quality situation in an all-round way.It is necessary to evaluate air quality.Accurate results of air quality evaluation can help people know more about air quality.In this paper,refers to previous research results and different evaluation methods,combined with artificial neural network,fuzzy theory,genetic algorithm,GA-BP hybrid algorithm based on fuzzy theory is proposed to evaluate air quality.At the same time,for the problem that the two-grade standard of air quality annual evaluation is not suitable for practical application,the four-grade standard for annual air quality evaluation has been proposed,and its practicality has been verified through experiments.By setting contrast experiments and comparing the air quality evaluation model based on standard BP algorithm,it is proved that the fuzzy GA-BP evaluation model is better than the standard BP model,both in efficiency and accuracy.

Ecological suitability evaluation for urban growth boundary in red soil hilly areas based on fuzzy theory

The fuzziness exists in spatial distribution of geographic data of land suitability evaluation processes,which makes it difficult to quantify land boundaries by using traditional binary logic-based overlay model.Aiming at this limitation,an ecological suitability evaluation analysis model was presented based on fuzzy theory and a research on urban growth boundary(UGB) of the Great-Hexi Leading District(GHLD) of Changsha was conducted.With the support of GIS,RS and MATLAB,slope,elevation,vegetation,soil productivity,soil permeability,water body and land use are selected as the input of model according to the characteristic properties of soil and terrain in red soil hilly areas.The running result of this model indicates that the ratios of highly suitable land,suitable land,moderately suitable land and unsuitable land in GHLD are 18.75%,10.31%,64.16%,6.78%,respectively.This result accords with spatial structure worked out by Space Development Strategy Planning of GHLD,Based on this result,several suggestions are made to guide UGB developments in future.

Application of Matter-element Model in Soil Nutrient Evaluation of Ecological Fragile Region

On the basis of the soil environment investigation in Da＇an City, Jilin Province, China, 40 soil samples from main land use types were obtained and tested by standard method. Soil organic matter （SOM）, total N （TN）, total P （TP）, total K （TK）, available N （AN）, available P （AP） and available K （AK） were chosen as the evaluation factors. A regional soil nutrient evaluation model was developed based on the matter-element model. The results show that the soil samples with nutrient grade Ⅱ-Ⅴ respectively account for 10%, 30%, 32.5% and 27.5%, and those with grade Ⅳ and Ⅴ account for 60% in all samples. The relationship between soil nutrients and land types indicates that the nutrients of farmland are relatively good, with 41.7% of soil samples with the nutrient grade Ⅳ and Ⅴ. The nutrients of saline-alkali land and sandy land are the worst, with 100% of soil samples with the nutrient grade IV and V. And the ratios of soil samples grade IV and V in grassland and wasteland are respectively 62.5 % and 54.55%. Generally speaking, the soil nutrients status in Da＇an City is poor, 60% of soil samples are in poor and extremely poor conditions, indicating that the soil has been severely eroded. Being a relatively superior evaluation method with more accurate resuits and spatial distribution consistency, matter-element analysis is more suitable for regional soil nutrient evaluation than previous models.

An algorithm based on evidence theory and fuzzy entropy to defend against SSDF

In cognitive radio networks, spectrum sensing is one of the most important functions to identify available spectrum for improving the spectrum utilization. Due to the open characteristic of the wireless electromagnetic environment, the wireless network is vulnerable to be attacked by malicious users(MUs), and spectrum sensing data falsification(SSDF) attack is one of the most harmful attacks on spectrum sensing performance. In this article,an algorithm based on the evidence theory and fuzzy entropy is proposed to resist SSDF attacks. In this algorithm, secondary users(SUs) obtain the corresponding degree of membership function and basic probability assignment function based on the local energy detection result. The new conflicting coefficient is calculated based on the evidence distance and classical conflicting coefficient, and the conflicting weight of the evidence is obtained.The fuzzy weight is calculated by the fuzzy entropy. The credibility weight is obtained by updating the credibility. On this basis, the probability assignment function of the evidence is corrected, and the final result is obtained by using the fusion formula. Simulation results show that the proposed algorithm has a higher detection probability and lower false alarm probability than other algorithms.It can effectively defend against SSDF attacks and improve the performance of spectrum sensing.

Using Fuzzy Theory and Variable Weights for Water Quality Evaluation in Poyang Lake, China

Achieving water purity in Poyang Lake has become a major concern in recent years, thus appropriate evaluation of spatial and temporal water quality variations has become essential. Variations in 11 water quality parameters from 15 sampling sites in Poyang Lake were investigated from 2009 to 2012. An integrative fuzzy variable evaluation(IFVE) model based on fuzzy theory and variable weights was developed to measure variations in water quality. Results showed that: 1) only chlorophyll-a concentration and Secchi depth differed significantly among the 15 sampling sites(P < 0.01), whereas the 11 water quality parameters under investigation differed significantly throughout the seasons(P < 0.01). The annual variations of all water quality variables except for temperature, electrical conductivity, suspended solids and total phosphorus were considerable(P < 0.05). 2) The IFVE model was reasonable and flexible in evaluating water quality status and any possible ′bucket effect′. The model fully considered the influences of extremely poor indices on overall water quality. 3) A spatial analysis indicated that anthropogenic activities(particularly industrial sewage and dredging) and lake bed topography might directly affect water quality in Poyang Lake. Meanwhile, hydrological status and sewage discharged into the lake might be responsible for seasonal water quality variations.

New Image Recognition Method Based on Rough-Sets and Fuzzy Theory

A new image recognition method based on fuzzy rough sets theory is proposed, and its implementation discussed. The performance of this method as applied to ferrography image recognition is evaluated. It is shown that the new method gives better results than fuzzy or rough sets method when used alone.

Evaluaton model for the geometry complexity of casting based on fuzzy theory

The parameters that describe the complex degree of a certain casting are of some uncertainty. Therefore, a new method based on the fuzzy theory to classify the complex degree of castings has been presented in this paper. The feasibility of fuzzy theory in describing the complex degree of castings has been discussed and the procedure of this method has been specified by analyzing the complex degrees of some typical castings. The element factors that influence the casting complexity, have been summarized, which include the wall-thickness and the number of transition surface, etc. The results show that it is reasonable and practicable to classify the complex degree of castings with the fuzzy theory.