Pattern design and optimization of yarn-dyed plaid fabric using isolation niche genetic algorithm and rough set theory

Under the circumstance of perceptual consumption, it is still challenging to grasp consumer's emotions and demands due to the large search space, diversified preferences, and easy fatigue of consumers. To reduce user fatigue and enlarge search space, a novel method was presented to design and optimize the pattern of yarn-dyed plaid fabric using the isolation niche genetic algorithm and rough set theory. Each pattern was encoded as a chromosome based on the real number code. The population was initialized and evolved using INGA to maintain the diversity. The rough set theory was adopted as the fitness function of isolation niche genetic algorithm to extract the consumer's demands. After multiple evolutions, a large set of practical patterns of the yarn-dyed plaid fabric are obtained. Experiments were carried out by 24 testers of different ages and genders. The results prove that the proposed method based on the isolation niche genetic algorithm and rough set theory is feasible and effective, supplying references to the designer.     

Distance and similarity measures of Pythagorean fuzzy sets based on the Hausdorff metric with application to fuzzy TOPSIS

Pythagorean fuzzy sets (PFSs) were proposed by Yager in 2013 to treat imprecise and vague information in daily life more rigorously and efficiently with higher precision than intuitionistic fuzzy sets. In this paper, we construct new distance and similarity measures of PFSs based on the Hausdorff metric. We first develop a method to calculate a distance between PFSs based on the Hasudorff metric, along with proving several properties and theorems. We then consider a generalization of other distance measures, such as the Hamming distance, the Euclidean distance, and their normalized versions. On the basis of the proposed distances for PFSs, we give new similarity measures to compute the similarity degree of PFSs. Some examples related to pattern recognition and linguistic variables are used to validate the proposed distance and similarity measures. Finally, we apply the proposed methods to multicriteria decision-making by constructing a Pythagorean fuzzy Technique for Order Preference by Similarity to an Ideal Solution and then present a practical example to address an important issue related to social sector. Numerical results indicate that the proposed methods are reasonable and applicable and also that they are well suited in pattern recognition, linguistic variables, and multicriteria decision-making with PFSs.     

基于改进粗糙集理论的SAR图像目标增强

图像增强在提高SAR图像舰船目标检测精度方面具有十分重要的意义。由于传统算法不能很好地对SAR图像进行目标增强，提出了基于改进粗糙集理论和引力场强度的目标增强算法。通过借鉴引力场相关理论知识，将粗糙集条件属性集中的梯度属性改进为引力场强度属性，从而实现对原图像的目标增强。与其他算法进行了实验比较，结果表明提出的改进算法相比于其他算法更适用于SAR图像特性，能更好地对舰船目标像素进行针对性增强，具备一定的工程应用价值。     

Chest X-ray enhancement to interpret pneumonia malformation based on fuzzy soft set and Dempster–Shafer theory of evidence

Image enhancement algorithms are commonly used to increase the contrast and visual quality of low-dose x-ray images. This paper proposes an automated enhancement method using soft fuzzy sets with a new decision-making scheme based on Dempster-Shafer theory of evidence for the visual interpretation of pneumonia malformation in low-dose x-ray images, called as XEFSDS. The XEFSDS model first generates an original source x-ray image into a complementary image, then each original and complement image is applied to the characterized image object and background areas of fuzzy space. The S-function is utilized to define fuzzy soft sets for the classification of gray level ambiguity in both images, and hence a decision criterion via Dempster-Shafer approach and fuzzy interval has been adapted to discriminate uncertainties on the pixel intensity and the spatial information. Modified membership grade operations have been performed on each object/background area, and Werner’s AND/OR operator (an aggregation operator) has been utilized to build a new membership function from two modified membership functions. Finally, an enhanced image is obtained from the new membership function via defuzzification. Experiments on different pneumonia X-ray images demonstrate that the XEFSDS scheme produces better results than the existing methods. To show the advantages of the XEFSDS scheme, we have executed a segmentation based examination on enhanced image for the detection of pneumonia malformation as well as abnormal lobe (lobar pneumonia) or bronchopneumonia.     

絮体表面形态对膜污染预测的影响

现有对混凝-膜过滤过程中膜污染的预测分析，一般采用XDLVO理论对光滑界面的作用能进行计算，但混凝絮体表面形态会对预测结果产生较大的影响。利用正弦波球体模型对粗糙腐殖酸(HA)絮体表面进行模拟，并通过表面元素积分法(SEI)结合XDLVO理论与复合辛普森规则，对不同粗糙程度的混凝絮体与聚偏氟乙烯(PVDF)膜的界面作用能进行量化模拟；并将结果与传统XDLVO理论模拟的光滑界面作用能进行了比较。实验结果表明，该模型适用于混凝-膜过滤体系中絮体界面作用能的模拟，同时在模拟过程中，由于粗糙度的不同会导致界面作用能在数值上存在1~2个数量级的差异；并且粗糙的絮体较完全光滑的絮体与膜污染趋势的拟合程度更高，即引入絮体表面形态对利用絮体与膜界面间相互作用能表征膜污染趋势的置信度更高。     

基于工业机器人的液压支架导向套柔性制造系统

自动化技术在小批量多品种的产品制造中，存在兼容难、换产时间长、人工干预多等问题，导致生产线难以高效率运行。设计的柔性制造系统，在充分分析了导向套不同结构、不同规格的基础上，以一套六关节机器人和行走地轨作为物流搬运设备，同时负责3台数控设备、自动辊道上料设备、自动堆垛下料设备、翻转机构、打标机构及抽检机构的上下料，并通过使用机器人双工位卡爪、机床六爪卡盘、自动刀补等卡具及技术，实现了一键换产，极大提高了制造系统的柔性。     

基于改进的RS-TOPSIS模型的岩爆倾向性预测

针对目前岩爆倾向性中预测模型权重确定存在不足导致模型精度不高的现状，为更准确地预测岩爆倾向性，提出综合运用粗糙集理论中的代数观和信息观，确定属性最优权重，并修正岩爆倾向性与评价指标之间的关系，建立岩爆等级理想点矩阵。根据岩爆发生条件，选取岩石脆性指数、切应力指标和弹性应变能指数3项指标作为岩爆判别指标，以国内外20组典型岩爆数据为样本，建立改进的粗糙集—理想点法（RS-TOPSIS）岩爆倾向性预测模型，并应用该模型对玲珑金矿等工程实际进行了岩爆倾向性预测。结果表明：改进后样本预测精度相比于改进前有了显著提高，所建立的模型对实际工程的岩爆倾向性预测效果良好，预测结果更准确。