煤与瓦斯突出预报的模糊聚类关联分析法

首先采用模糊聚类分析对煤与瓦斯突出的样本集合进行分类，建立不同突出程度的模糊模式。然后用关联分析确定待预报样本与模式的关联程度，以此预测预报样本的煤与瓦斯突出危险程度。这种预报方法相对于模糊聚类分类后，将模式与待预报样本组成新的样本集合，再进行聚类分析，以此分类结果进行预报法。不仅可靠程度高，而且能定量描述待报样本与模式的亲和程度。     

暂态电路的试验设计

在电工电子技术暂态电路的试验设计中，因电路本身响应时间短，用常规仪器很难对其响应的过程进行直接测量。本文结合暂态电路的工作原理及常规仪器的特点，给出三种简单、实用的试验电路设计方法。     

山雨欲来风满楼——复旦大学胡爱本教授谈中国并购潮

截至去年年底,中国国内企业的并购总金额已经达到1200多亿元,目前中国国内企业并购呈加速状态,中国并购的高潮正在酝酿。未来进行并购活动的买方和卖方都将呈现“爆炸性的增长”。 那么,我国的并购有什么特点?又将如何发展?最近,本刊专访复旦大学博士生导师胡爱本教授,他在企业战略管理和人力资源管理方面有很深的造诣。     

葛的研究及其开发利用状况

中国是葛属植物原产中心，除西藏、青海和新疆外各省区分布有11种，部份省区已有相当规模的人工栽培，已有为数不多的优良品种用于生产，我市引种无渣粉葛已获成功．葛根主要成分是异黄酮类化合物、淀粉、多种必需氨基酸和矿物元素。根提取物制药用于临床可有效治疗冠心痛，心绞痛等多种疾病。国内外已开发出众多功能性绿色食品。葛集经济作物、优良牧草和水土保持植物特点于一身，是退耕还草发展有机农业的首选经济作物。     

Samples Selection for Artificial Neural Network Training in Preliminary Structural Design

An artificial neural network (ANN) is applied in the preliminary structural design of reticulated shells. Major efforts are made to enhance the generalization ability of networks through well-selected training samples. Number-theoretic methods (NTMs) are adopted to generate samples with low discrepancy, i.e.uniformly scattered in the domain, where discrepancy is a quantitative measurement of the uniformity. The discrepancy of the NTM-based sample set is 1/6-1/7 that of samples with equal spacing. In a case study,networks trained by NTM-based samples are compared with those trained by equal-spaced samples in generalizing performance. The results show that both the computational precision and stability of the former ANNs are more satisfactory than those of the latter. It is concluded that the flexibility of ANNs in generalizing can be effectively increased by use of uniformly distributed training samples rather than simply piling data.More reliable uniformity should be obtained, however, through NTMs instead of equal-spaced samples.     

复合型材料电子技术人才知识结构及课程设置的研究与实践

通过材料电子复合型工程技术人才培养目标和课程设置的讨论,提出了“3 3”三主三副的专业方向和“3 3 4”的知识能力素质结构。