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.     

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。     

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。     

基于机器视觉的运煤车车号识别技术研究

在铁路运煤装车过程中为了快速、准确地识别车号,提出一种基于机器视觉的运煤车车号识别技术。将连通区域提取与投影分割法结合,实现车号的粗定位、细分割,并对图像中的断裂字符进行二次分割,构建了基于BP神经网络的分类模型进行车号识别,提升了煤炭装车的效率和精度。     

Optimization of Sentiment Analysis Using Teaching-Learning Based Algorithm

Feature selection and sentiment analysis are two common studies that are currently being conducted; consistent with the advancements in computing and growing the use of social media. High dimensional or large feature sets is a key issue in sentiment analysis as it can decrease the accuracy of sentiment classification and make it difficult to obtain the optimal subset of the features. Furthermore, most reviews from social media carry a lot of noise and irrelevant information. Therefore, this study proposes a new text-feature selection method that uses a combination of rough set theory (RST) and teaching-learning based optimization (TLBO), which is known as RSTLBO. The framework to develop the proposed RSTLBO includes numerous stages: (1) acquiring the standard datasets (user reviews of six major U.S. airlines) which are used to validate search result feature selection methods, (2) pre-processing of the dataset using text processing methods. This involves applying text processing methods from natural language processing techniques, combined with linguistic processing techniques to produce high classification results, (3) employing the RSTLBO method, and (4) using the selected features from the previous process for sentiment classification using the Support Vector Machine (SVM) technique. Results show an improvement in sentiment analysis when combining natural language processing with linguistic processing for text processing. More importantly, the proposed RSTLBO feature selection algorithm is able to produce an improved sentiment analysis.     

带权决策表的属性约简

属性约简是粗糙集理论的重要应用。考虑将决策表中的每行都作为一条决策规则时，若把表中出现相同决策规则的次数作为权，可得到带权决策表。提出了关于带权决策表的正域约简相应的辨识矩阵并给出了证明，从而得到了约简算法。相比于决策表中的正域约简时发现，通过将决策表转化为带权决策表后，再利用算法1进行约简时，其在一定程度上优于前者。提出了近似分类精度约简相应的辨识矩阵并给出了证明。对于2个算法，在选取的UCI数据集上进行了实验验证。通过实验进一步说明了所提出算法的可行性和有效性。     

直线运动滚动导轨副混合润滑研究

综合考虑了直线运动导轨副接触几何、预紧力、真实表面粗糙度、曲率系数等因素,建立了直线运动导轨副混合润滑数值模型,研究了滑块移动速度、曲率半径系数、工作载荷、表面粗糙度对导轨接触副润滑特性的影响,得到结论:导轨副法向工作载荷、最大赫兹接触压力和赫兹接触半径随着外加总载荷的增大而增大,平均膜厚随着载荷的增大而减小;混合润滑模型可预测导轨副在大范围工况条件下完整的润滑状态;直线运动导轨大多工作在混合润滑状态下,随着滑块移动速度的增加,接触界面由边界润滑状态向混合润滑状态转变,润滑性能逐渐提高;适当增加曲率半径系数,有利于润滑油膜的形成与稳定。     

基于未确知集对联系数法的溃坝社会影响评价

针对溃坝社会影响因素的不确定性和复杂性易造成评价过程信息缺失的问题,采用未确知测度理论和层次分析法,将其不确定信息转换为具有相对确知信息的综合测度向量,结合集对分析可有效处理研究系统的确定性与不确定性关系的特点,引入五元集对联系数,建立了基于未知集对联系数法的溃坝社会影响评价模型,以未确知集对联系数所属区间的等级作为溃坝社会影响严重程度等级判定的依据,并通过工程实例验证了所建溃坝社会影响评价模型的合理性和有效性,为溃坝社会影响评价提供了一种新的方法和思路。