Random Group Recommendation Model Based on Fuzzy Clustering

The group recommendation system is a viral requirement for the Internet service provider to provide recommendation services for all the users in a group. Due to the shared or different interests among users in the group, it is difficult for traditional personal recommendation algorithms to predict items that can meet the requirements of all the users in the group. In this paper, a random group recommendation model is proposed to recommend the top K most appealing items for all the users in a random group. By analyzing item ratings of all the users in the group, the recommendation model can abstract the group as a virtual user. Then a personal recommendation algorithm is applied to suggest the top K most appealing items for the virtual user. And the preference score and fuzzy clustering algorithm based on multiclass are applied to optimize the recommendation result of the group recommendation model. Finally, the MovieLens-100K dataset is applied to verify the efficiency of the recommendation model. The experimental results show that the items recommended by the proposed group recommendation model are more popular for all the users in the group than the items recommended by traditional group recommendation algorithms.     

Some realizations and instances of Yager prioritized preference frame with application in evaluation and decision making

This study first revamps Yager prioritized ordered weighted averaging operators, and condenses them into a conceptual frame with putting aside one realization from Yager's original proposal. Then, based on elicited conceptual frame called Yager prioritized preference conceptual frame, this article proposes three distinct realizations to the conceptual frame with corresponding different instances, in which some evaluation models with weights determination methods are provided. Numerical examples are also presented immediately after every instance. Lastly, this study proposes the concepts of outer monotonic, inner monotonic, and global monotonic weights functions, and discusses some related properties, which are often embodied in preferences of decision makers.     

Pythagorean linguistic preference relations and their applications to group decision making using group recommendations based on consistency matrices and feedback mechanism

In this paper, we introduce a new type of fuzzy set, called Pythagorean linguistic sets (PLSs), to address the preferred and nonpreferred degrees of linguistic variables. Moreover, it allows decision makers to offer effectively handle uncertain information more flexible than intuitionistic linguistic sets (ILSs) when one compares two alternatives in the process of decision making. Some of the fundamental operational laws, score, accuracy, and aggregation operators are defined, and their properties are investigated. Preference relation (PR) is a useful and efficient tool for decision making that only requires the decision makers to compare two alternatives at one time. Taking the advantages of PLSs and PRs, this paper also introduces Pythagorean linguistic preference relations (PLPRs) and studies their application. We propose an approach for group decision making using group recommendations based on consistency matrices and feedback mechanism. First, the proposed method constructs the collective consistency matrix, the weight collective PRs, and the group collective PRs. Then, it constructs a consensus relation for each expert and determines the group consensus degree (GCD) for all experts. If the GCD is smaller than a predefined threshold value, then a feedback mechanism is activated to update the PLPRs. Finally, after the GCD is greater than or equal to the predefined threshold value, we calculate the arithmetic mathematical average values of the updated group collective PR to select the most appropriate alternative.     

基于动态模糊推理的舒适温度在线预测

基于热感觉预测的室内热环境自动控制方法为解决基于传统温度设定值控制不满足用户舒适度问题提供新的途径。但建模过程中用户热感觉信息难以获取,因此开发了便捷的移动端智能交互系统以实时采集现场数据,建立用户学习样本;并针对热舒适的动态变化性特征,设计动态进化神经模糊推理系统(DENFIS)以建立用户热舒适在线预测模型。通过实时学习样本数据驱动,系统的模糊规则与模型输出函数系数可动态自校正,推理预测出用户偏好温度。实验结果表明所设计的DENFIS算法预测用户的舒适温度范围准确率高达90.5%,误差极小。证明了该算法所建立的在线预测模型用于智能空调温度控制,可解决现有的温度设定方式带来的温度设定值不合理的问题,在实际应用中具有可行性。     

融合FAHP 和TOPSIS 的适老化产品综合评价与优选方法——以老年智能手环为例

为了更全面地对适老化智能手环进行综合评价,进而辅助最终的方案评价与优选, 从产品设计、用户体验、人机交互和实际生产4 个维度构建了适老化智能手环的评价模型。首 先采用基于三角模糊数的层次分析法(FAHP)计算出各项评价准则的权重,然后采用逼近理想解 排序法(TOPSIS)对若干备选方案做出评价并完成排序,最后根据结果进行方案的综合评价与优 选。以某品牌16 款适老化智能手环的备选方案为例,证明FAHP-TOPSIS 法的可行性,发挥其 现实意义。该评价优选方法,在考虑人的思维模糊性的基础上,从系统与层次等多个角度将思 维过程进行定性与定量分析,从而为适老化智能手环方案的优选问题提供清晰适合的决策方案 与优化思路。     

Improvement of risk assessment in the FMEA using nonlinear model,revised fuzzy TOPSIS,and support vector machine

In every organization, performing accurate risk assessment along with consideration of increasing accidents is a necessary tool to prevent and reduce the fatal and non-fatal consequences of their occurrence. One of the most popular methods of risk assessment is Failure Mode and Effects Analysis, which evaluate failure modes in a system by using risk priority numbers (RPNs). These methods have been criticized for including several deficiencies such as the effect of personal ’opinions, the same importance of the factors and risk rating. The present work utilizes a hybrid approach based on support vector machine and fuzzy inference system to decrease the effect of personal's opinions in determining the factors of the severity and occurrence. Also, Logarithmic Fuzzy Preference Programming is used to determine the crisp weight of dependent factor of FMEA and revised fuzzy TOPSIS used for more accurate ranking of risks. One main feature of the proposed model is that it can be used to evaluate safety risks in all organizations. To investigate the suitability of this approach, the proposed model was presented in the Copper leaching factory, Kerman, Iran. The results showed that this model has the ability to predict severity and occurrence refers to occupational accidents which occurred in a 5-year period (2012–2017) with accuracy of 87% and 95%, respectively. Also, based on the results, it was found that the weights of severity, occurrence, and detection were 0.479, 0.335, and 0.186, respectively. Results of the ranking process showed that the risk of fall from height and stucking between the objects had the highest and the lowest priority, respectively.     

An interindividual iterative consensus model for fuzzy preference relations

Consensus reaching models are widely used to derive a representative solution in group decision-making problems. Current models present limitations regarding the achievement of the agreement and keeping enough consistency for achieving valid solutions. Therefore, this paper proposed a new consensus model based on the deviation degree of two fuzzy preference relations (FPRs), in which a novel consistency index (CI) is defined to measure whether an FPR is of acceptable consistency. Additionally, an interindividual similarity index (ISI) is devised to measure the consensus degree of two FPRs. In the proposed consensus reaching process, ISI is also used to guide the two most incompatible decision-makers (DMs) to modify their judgments. The proposed iterative consensus reaching algorithm is convergent, CI preservation. After that, a stationary vector method is adopted to determine DMs’ weights for the aggregation process based on DMs’ opinion transition probabilities. Finally, an illustrative example and comparative analysis is given to demonstrate the effectiveness of the proposed model.     

基于沉浸理论的自闭症儿童体感游戏交互设计

目的 探究可提升自闭症儿童体感游戏用户体验的交互设计方法,提升自闭症儿童在利用体感游戏进行康复训练时的用户体验.方法 以沉浸理论为基础,通过用户研究总结出自闭症儿童体感游戏的设计策略.并将层次分析法(AHP)和逼近理想解排序法(TOPSIS)应用到体感游戏的设计中,以及时的反馈、愉悦的界面表现、有效的操作交互、清晰的目标任务设计策略建立了体感游戏沉浸感设计的量化评估模型,并对设计出的方案进行了评估,选择了最佳方案,并进行深入的设计.结论 总结出了一套自闭症儿童体感游戏的交互设计策略和评估方法,并将其应用到自闭症儿童的体感游戏的设计中,从而创造出科学有效的沉浸式游戏体验,提高游戏干预自闭症儿童康复训练的效果,并为同类产品的设计提供了参考.     

基于个体偏好的老年橱柜物品收纳策略

目的 解决老年人厨房物品在橱柜系统收纳时个体偏好存在不确定性致使获取的收纳偏好存在偏差的问题,提出基于个体偏好的橱柜物品收纳策略.方法 首先,通过启发式访谈获取橱柜物品收纳的需求信息,因子分析提取需求核心因素,构建需求层级结构;其次,提出需求层级中收纳区域规划存在偏好的不确定性,通过对直接问询、联合分析及入户观察分别获取的收纳偏好进行比较分析,识别偏好中的不确定成分,通过一致性评判得出更为准确的偏好信息;最后,采用产品轮廓法将不同方法获取的收纳偏好信息转换为收纳区域划分方案,通过受测者评价,提炼出个体层面最优收纳区域划分方案;结论 单独采用主观直接问询或客观定量联合分析法,都不能准确获取老年橱柜物品收纳偏好,通过采用一致性评判的方法路径将多种方法得出偏好结果进行分析,可以更准确地获取老年橱柜区域划分需求偏好,为老年橱柜储物功能设计提供启发与参考.     

文创产品特质的多维测量与喜好度关系研究

目的 研究文创产品特质的构成与消费喜好度之间的关系.方法 以市面上代表性的文创产品为研究对象,采用统计学软件SPSS19.00中的多向度(MDS)分析模块对文创产品的特质进行测量,结合相关与回归分析模块论证文创产品特质与产品喜好度之间的关系,进而对文创产品特质强度与消费喜好度之间进行比较分析.结论 不同文创产品的特质强度与消费者的产品喜好度成因并不一致,生活中高频使用的产品,其产品的特质强度与喜好度的对应关系高,而低频使用的产品,其产品的特质强度与喜好度的对应关系低.此方法能够在准确测量文创产品特质强度的基础上,对比产品特质强度与消费者喜好度成因之间的关系,为文创产品开发设计策略的制定提供理论依据,也能为文创产品的可持续发展提供理论支撑.