On Fuzzy Conformable Double Laplace Transform with Applications to Partial Differential Equations

The Laplace transformation is a very important integral transform,and it is extensively used in solving ordinary differential equations,partial differential equations,and several types of integro-differential equations.Our purpose in this study is to introduce the notion of fuzzy double Laplace transform,fuzzy conformable double Laplace transform(FCDLT).We discuss some basic properties of FCDLT.We obtain the solutions of fuzzy partial differential equations(both one-dimensional and two-dimensional cases)through the double Laplace approach.We demonstrate through numerical examples that our proposed method is very successful and convenient for resolving partial differential equations.

Maximum Power Point Tracking Using Fuzzy Logic Controller under Partial Conditions

This study proposes a fuzzy system for tracking the maximum power point of a PV system for solar panel. The solar panel and maximum power point tracker have been modeled using MATLAB/Simulink. A simulation model consists of PV panel, boost converter, and maximum power point tack MPPT algorithm is developed. Three different conditions are simulated: 1) Uniform irradiation;2) Sudden changing;3) Partial shading. Results showed that fuzzy controller successfully find MPP for all different weather conditions studied. FLC has excellent ability to track MPP in less than 0.01 second when PV is subjected to sudden changes and partial shading in irradiation.

Adaptive neuro-fuzzy interface system for gap acceptance behavior of right-turning vehicles at partially controlled T-intersections

Gap acceptance theory is broadly used for evaluating unsignalized intersections in developed coun tries. Intersections with no specific priority to any move ment, known as uncontrolled intersections, are common in India. Limited priority is observed at a few intersections, where priorities are perceived by drivers based on geom etry, traffic volume, and speed on the approaches of intersection. Analyzing such intersections is complex because the overall traffic behavior is the result of drivers, vehicles, and traffic flow characteristics. Fuzzy theory has been widely used to analyze similar situations. This paper describes the application of adaptive neurofuzzy interface system （ANFIS） to the modeling of gap acceptance behavior of rightturning vehicles at limited priority Tintersections （in India, vehicles are driven on the left side of a road）. Field data are collected using video cameras at four Tintersections having limited priority. The data extracted include gap/lag, subject vehicle type, conflicting vehicle type, and driver＇s decision （accepted/rejected）. ANFIS models are developed by using 80 % of the extracted data （total data observations for major road right turning vehicles are 722 and 1,066 for minor road right turning vehicles） and remaining are used for model vali dation. Four different combinations of input variables are considered for major and minor road right turnings sepa rately. Correct prediction by ANFIS models ranges from 75.17 % to 82.16 % for major road right turning and 87.20 % to 88.62 % for minor road right turning. Themodels developed in this paper can be used in the dynamic estimation of gap acceptance in traffic simulation models.

一种Vague值转化Fuzzy值的偏联系数方法

针对Vague集与Fuzzy集,结合联系数理论,提出了一种基于Vague值转化为Fuzzy值的偏联系数方法。通过实例验证了该方法是合理可行且有效的。

Fuzzy集的偏熵与关联熵

在文献[1]的基础上,推广模糊熵的概念,首次定义Fuzzy集的偏熵、关联熵和关联熵系数等新概念。对其主要性质进行讨论,并与模糊散度建立联系,得到一些重要结果。

Vague值转化Fuzzy值的一种偏势方法

在联系数理论与Vague集理论基础上,提出了一种新的Vague值转化Fuzzy值的偏势方法.分析了相关文献的不足与缺陷,认为Vague值转化Fuzzy值的本质是对Vague值中未确知度趋向支持度的一种偏势变化.最后讨论了该转化方法满足的准则、可分辨性及可行性等,并通过实例比较了该方法的实用性.

一类超富足半群上的fuzzy好同余

引入了富足半群上fuzzy好同余的概念,给出了富足半群上fuzzy好同余的性质和特征.在此基础上,给出了超富足半群上fuzzy好同余的性质.最后,讨论了一类IC-超富足半群上的fuzzy好同余,得到了一些结果.

整体偏联系数与随机模拟耦合的水资源承载力评价方法

为定量评价区域水资源承载力、挖掘区域水资源承载力评价过程中的不确定性信息、合理构造集对分析联系数分量的迁移率矩阵,提出采用基于同异反总关系程度“a+b+c”度量的整体偏联系数方法计算得到修正联系数分量,再结合三角模糊数随机模拟方法,构建了基于整体偏联系数与随机模拟耦合的水资源承载力评价方法。文中模型在宿州市2011—2019年的应用结果表明:宿州市水资源承载能力总体偏低,除2018年以外,其余年份水资源承载力评价等级均在2级以上,但是评价等级有逐年下降趋势,水资源承载力呈现正向改善的趋势;水资源承载力级别特征值全部落在本文方法计算出的评价区间内,认为该方法合理,与基于偏联系数原理构造的迁移率矩阵计算的评级等级基本一致且误差更小,说明该方法在联系数分量迁移转化时更合理,可为判别区域水资源承载力评价等级、合理调控区域水资源承载力提供有效途径。

L-Fuzzy偏序集(英文)

借助 L-fuzzy关系在 L-fuzzy集中引入 L-fuzzy偏序 ,自然地有了 L-fuzzy偏序集 ,进一步借助水平截集刻画了 L -fuzzy偏序集。

连续论域上Fuzzy集的信息熵

在文献[1]的基础上,把模糊熵从离散论域推广到连续论域,给出连续论域上Fuzzy集的偏熵、关联熵等概念。对其主要性质进行讨论,取得了一些令人满意的结果。拓宽信息熵的研究领域,对不确定复杂系统的信息处理、知识学习、归纳学习、模糊信息学的进一步研究打下一定基础。

L-Fuzzy伴随的若干特征定理

研究 Frame格上的一类等价关系 ,给出 L - Fuzzy伴随的若干性质定理及其等价刻画 ,体现了L- Fuzzy伴随的层次伴随特点 ,最后引入广义 L-值偏序集的概念 ,得到了类似经典伴随的若干特征定理。

偏序集内保序映象的Fuzzy不动点定理

研究了在点式定义下的基本Ｆｕｚｙ点的偏序关系时的不动点定理，推广了经典情形时的相应结果．

Fuzzy横截和Fuzzy拟阵

本文引入了Fuzzy横截,部分Fuzzy横截的概念,证明了有限Fuzzy集族的全体部分Fuzzy横截是一个Fuzzy拟阵的全体Fuzzy独立集,给出并证明了有限Fuzzy集族具有Fuzzy横截的一个充要条件,最后利用Fuzzy点给出了Fuzzy拟阵的一个等价描述.

Vague值向Fuzzy值转化的系列方法

提出Vague值向Fuzzy值转化的系列均值法和偏值法.

Fuzzy Analytical Solution to Vertical Infiltration

In this article, we examine the solution of the fuzzy linear vertical infiltration equation, which represents the water movement in porous media in that part which is called the vadose zone. This zone is very important for semi-arid areas, due to complex phenomena related to the moisture content in it. These phenomena concern the interchange of moisture content between the vadose zone and the atmosphere, groundwater and vegetation, transfer of moisture and vapor and retention of moisture. The equation describing the problem is a partial differential parabolic equation of second order. The calculation of water flow in the unsaturated zone requires the knowledge of the initial and boundary conditions as well as the various soil parameters. But these parameters are subject to different kinds of uncertainty due to human and machine imprecision. For that reason, fuzzy set theory was used here for facing imprecision or vagueness. As the problem concerns fuzzy differential equations, the generalized Hukuhara (gH) derivative was used for total derivatives, as well as the extension of this theory for partial derivatives. The results are the fuzzy moisture content, the fuzzy cumulative infiltration and the fuzzy infiltration rate versus time. These results allow researchers and engineers involved in Irrigation and Drainage Engineering to take into account the uncertainties involved in infiltration.

Novel robust approach for constructing Mamdani-type fuzzy system based on PRM and subtractive clustering algorithm

A novel approach for constructing robust Mamdani fuzzy system was proposed, which consisted of an efficiency robust estimator(partial robust M-regression, PRM) in the parameter learning phase of the initial fuzzy system, and an improved subtractive clustering algorithm in the fuzzy-rule-selecting phase. The weights obtained in PRM, which gives protection against noise and outliers, were incorporated into the potential measure of the subtractive cluster algorithm to enhance the robustness of the fuzzy rule cluster process, and a compact Mamdani-type fuzzy system was established after the parameters in the consequent parts of rules were re-estimated by partial least squares(PLS). The main characteristics of the new approach were its simplicity and ability to construct fuzzy system fast and robustly. Simulation and experiment results show that the proposed approach can achieve satisfactory results in various kinds of data domains with noise and outliers. Compared with D-SVD and ARRBFN, the proposed approach yields much fewer rules and less RMSE values.

Analysis of Partial Volume Effects on Accurate Measurement of the Hippocampus Volume

Hippocampal volume loss is an important biomarker in distinguishing subjects with Alzheimer＇s disease （AD） and its measurement in magnetic resonance images （MRI） is influenced by partial volume effects （PVE）. This paper describes a post-processing approach to quantify PVE for correction of the hippocampal volume by using a spatial fuzzyC-means （SFCM） method. The algorithm is evaluated on a dataset of 20 T1-weighted MRI scans sampled at two different resolutions. The corrected volumes for left and right hippocampus （HC） which are 23% and 18% for the low resolution and 6% and 5% for the high resolution datasets, respectively are lower than hippocampal volume results from manual segmentation. Results show the importance of applying this technique in AD detection with low resolution datasets.

A Study on Associated Rules and Fuzzy Partitions for Classification

The amount of data for decision making has increased tremendously in the age of the digital economy. Decision makers who fail to proficiently manipulate the data produced may make incorrect decisions and therefore harm their business. Thus, the task of extracting and classifying the useful information efficiently and effectively from huge amounts of computational data is of special importance. In this paper, we consider that the attributes of data could be both crisp and fuzzy. By examining the suitable partial data, segments with different classes are formed, then a multithreaded computation is performed to generate crisp rules (if possible), and finally, the fuzzy partition technique is employed to deal with the fuzzy attributes for classification. The rules generated in classifying the overall data can be used to gain more knowledge from the data collected.

Fuzzy Ordered Filters in Implicative Semigroups

We fuzzify the concept of ordered filter in implicative negatively partially ordered semigroups and study its properties.

单边区间集模糊半概念的知识表示及提取方法

为了使“区间”形式加以表述的不确定信息的提取具有侧重性,需提取出对象(属性)集对应的属性(对象)区间集。本文在模糊形式背景中,通过引入2个阈值,将单边区间集与经典半概念结合,提取出属性(对象)集对应的对象(属性)区间集,从而提出区间集外延–集合内涵(集合外延–区间集内涵)(interval set extent-set intent(set extent-interval set intent),ISE-SI(SE-ISI))型单边区间集模糊半概念。全体ISE-SI(SE-ISI)型单边区间集模糊半概念构成格,并给出基于格搜寻全体ISE-SI(SE-ISI)型单边区间集模糊半概念的算法。通过与已有成果对比,显示出这2种知识表示形式的多方优势。本文所得结果在知识表示及提取方法上具有适用范围广、实际应用强等优点。