启发式教学探索与研究

启发式教学是提高教学质量的重要措施,在教学实践中越来越受重视,文章从启发式教学的本质特征,如何搞好启发式教学,以及启发式教学中应注意的几个问题等几方面进行了论述,以期能帮助教师在教学实践中更有效地运用启发式教学。     

Exploring the effect of heuristic factors on the popularity of user-curated ‘Best places to visit’ recommendations in an online travel community

In online travel communities, ‘Top-K best places to visit’ recommendations are gaining more attention from travelers due to their ubiquitous access to the Internet, but little empirical effort has been made to investigate what factors lead to the popularity of user-curated ‘best places to visit (BP2V)’ recommendations. This research therefore aims to identify and validate the heuristic factors affecting the popularity of BP2V recommendations. Based on the heuristic-systematic model (HSM) of persuasion, we derive recommender-related (i.e., recommender's identity disclosure, reputation, experience, and location of residency) and recommendation-related (i.e., number of places recommended, helpfulness rating, number of comments added, and length of recommendation) heuristic characteristics of BP2V recommendations and investigate their impact on recommendation popularity. In addition, this study examines the moderating effect of destination category (i.e., attractions, food, shopping, and activities) on the relationship between heuristic characteristics and the popularity of BP2V recommendations. Our empirical results, which were based on 565 ‘best places to visit in the U.S.’ recommendation postings from Qyer.com, a major online travel community in China, suggest that recommender's identity disclosure, reputation, number of places recommended, helpfulness rating, and length of recommendation are positively associated with recommendation popularity. We also found that the relationships between heuristic factors and the popularity of BP2V recommendations are contingent on destination category. This study will contribute to the body of knowledge on online travel communities and HSM and provide valuable implications for general travelers and managers in the tourism and hospitality industry.     

专业网站零输入导航引擎设计与实现

针对专业网站术语繁多,网络搜索专业性强的需求特点,设计了一个无需输入、只根据用户上网浏览的信息特点,自动提取与发掘用户需求的导航引擎,避免因用户专业水平所限,而无法搜索到大量专业信息。详细介绍了导航引擎的核心信息挖掘模块的设计原理和启发式挖掘算法,并对设计的算法进行了测试与分析。     

资金和风险约束下的多产品报童模型最优解的研究

通过考虑近年来比较热门的多产品报童问题。以资金约束为第一约束,风险约束为第二约束,从而构成四种组合。在风险的刻画上,采用半方差来衡量;在资金约束的限制下,采用两种启发式算法来简化运算,通过实现费用函数的最小化来寻求满足约束条件的最优订购量。最后对文中叙述的结论加以数值分析。     

The effects and side-effects of statistics education: Psychology students’ (mis-)conceptions of probability

In three studies we looked at two typical misconceptions of probability: the representativeness heuristic, and the equiprobability bias. The literature on statistics education predicts that some typical errors and biases (e.g., the equiprobability bias) increase with education, whereas others decrease. This is in contrast with reasoning theorists’ prediction who propose that education reduces misconceptions in general. They also predict that students with higher cognitive ability and higher need for cognition are less susceptible to biases. In Experiments 1 and 2 we found that the equiprobability bias increased with statistics education, and it was negatively correlated with students’ cognitive abilities. The representativeness heuristic was mostly unaffected by education, and it was also unrelated to cognitive abilities. In Experiment 3 we demonstrated through an instruction manipulation (by asking participants to think logically vs. rely on their intuitions) that the reason for these differences was that these biases originated in different cognitive processes.     

产品定制过程中的顾客适应性决策行为研究

应用情境实验方法研究顾客在产品定制过程中的适应性决策行为,重点分析定制任务的复杂性如何影响顾客的定制策略.同时分析了顾客知识水平和任务参与程度两个因素对于适应性决策行为的调节作用.研究发现:定制任务的复杂程度增加,使用启发式策略的频率也增加;顾客知识水平与加权式策略使用频率负相关,而与启发式策略使用频率正相关;与之相反,任务参与程度与加权策略的使用频率正相关,而与启发式策略的使用频率负相关.     

可用性评价之启发式评价法在图书馆网站设计中的应用

对网站设计进行可用性评价,是成功的界面设计的必经阶段.在众多的评价方法中,启发式评价法是一种经典的可用性诊查方法.文章详细介绍了将可用性测试与启发式评价法运用于图书馆网站设计,以提高网站质量,提高可用性,更好地满足用户需要.     

启发式的属性值约简在隐形眼镜诊断中的应用

根据粗糙集理论,讨论属性值的约简方法。属性值约简是在属性约简的基础上,对决策表中的每一条记录去掉冗余属性值,从而构成一个最小的决策规则集。重点根据启发式值约简方法,对隐形眼镜数据进行分析,为后序的数据分析减少冗余信息。     

Scheduling of household power consumption for Step and Time-of-Use tariff system

This paper proposes a hybrid optimization to solve the scheduling of household power consumption for Step and Time-of-Use (TOU) tariff system. The target function is the cost of electricity, and the optimization object is total instantaneous power within a billing period. The control variables are starting moments of each household appliance. The optimization procedure is divided into two stages. Firstly, the prerequisite for minimal cost is calculated through mathematical analysis and generalized function theory. Secondly, the solution is obtained by using a heuristic algorithm in which the result of the first stage is considered to reduce the searching space. And an evaluation methodology is deduced to evaluate the optimization. The computer simulation demonstrates that the proposed approach can reduce the cost of electricity evidently in the sense of probability. The approach shows great value for embedded applications.     

基于RBFNN和HDP方法的蔗糖生产澄清工段中和pH值优化控制器的研究

澄清工段是亚硫酸法生产蔗糖的关键过程之一,而pH值又是该过程最关键的工艺指标,能否将其pH值稳定地控制在要求范围将影响整个糖厂产量和白糖质量．由于该过程是一个复杂的物理、化学过程,具有多输入、大滞后、强非线性、时变参数等特点,因此该过程pH值的稳定控制和优化问题一直没有得到很好的解决．采用径向基函数神经网络（RadialBasisFunctionNeuralNetwork,RBFNN）来建立该过程的神经网络模型．然后利用RBFNN来设计基于启发式动态规划（HeuristicDynamicProgramming,HDP）方法的优化控制器．仿真结果表明该方法可以取得满意的控制效果,为解决复杂非线性动态系统的优化控制问题提供了一种新途径．