Application of the relevance vector machine to canal flow prediction in the Sevier River Basin

This work addresses management of water for irrigation in arid regions where significant delays between the time of order and the time of delivery present major difficulties. Motivated by improvements to water management that will be facilitated by an ability to predict water demand, it employs a data-driven approach to developing canal flow prediction models using the relevance vector machine (RVM), a probabilistic kernel-based learning machine. A search is performed across model attributes including input set, kernel scale parameter and model update scheme for models providing superior prediction capability using the RVM. Models are developed for two canals in the Sevier River Basin of southern Utah for prediction horizons of up to 5 days.     

基于可信多数投票的快速概念漂移检测

数据流因具有数据持续到达，概念漂移产生时刻无法预测、概念的数量不确定等特征，使得滑动窗口的大小很难事先确定，滑动窗口包含概念的数量对概念漂移检测存在影响.本文提出了基于可信多数投票的快速概念漂移检测算法（CMV_SEA），该算法使用SEA算法中的基分类器淘汰方法，使用可信多数投票实现滑动窗口中基分类器的集成.仿真实验表明：相比于SEA算法，CMV_SEA算法提高了泛化能力；能在新概念产生的第一时间内检测到概念漂移；对概念漂移的检测能力和新概念的学习能力不受滑动窗口大小的影响.     

Connecting market orientation,learning orientation and corporate social responsibility implementation: is innovativeness a mediator?

Corporate social responsibility (CSR) has been a topic of interest to both practitioners and researchers in the forest products sector. However, the existing literature falls short of examining the connections between CSR implementation and firm cultures, a key link to further our understanding for CSR implementation. This current study investigates the relationship between firm cultures and CSR implementation in the global forest, paper & packaging industry companies. Specifically, the authors propose firm cultures, including market orientation, learning orientation and innovativeness potentially support CSR implementation. Also, innovativeness is proposed to mediate the market orientation-CSR and learning orientation-CSR relationships. Data are collected through a mail survey with responses from 58 companies (87 individuals) of the Top 100 global forest, paper & packaging industry companies, identified by PricewaterhouseCoopers in its 2008 Global Forest, Paper & Packaging Industry Survey. Results confirm the hypothesized relationships between market orientation and CSR and learning orientation and CSR. However, the proposed mediating effect of innovativeness is not significant.     

21世纪高校学生工作发展趋势初探

２１世纪信息时代的到来和高等教育改革的不断深化，对我国高校学生工作提出了严峻的挑战。在这种新的形势下，高校学生工作将呈现五种发展趋势。     

论农业高等教育与农业的可持续发展

本以高等教育在未来经济发展中所占有的重要地位为出发点，分析了科学人主义教育观与持续发展思想间的契合关系，着重阐述了实施农业可持续发展战略中化力的作用特别是农业高等教育在优化人环境中的作用。     

基于Elman小波神经网络的垦区地下水位预测模型研究

在现有Elman神经网络和小波分析理论研究的基础上,提出了Elman小波神经网络模型。给出了Elman小波神经网络梯度下降法训练的推导过程,为了避免梯度下降法收敛速度慢、容易产生振荡和陷入局部最优等缺点,在Elman小波神经网络的训练过程中引入动量项和自适应学习速率,并将该网络应用到垦区地下水位预测中,取得了良好的预期效果。在训练过程中,该网络具有收敛速度快,精度高等优点,同时也具有较好的泛化能力。     

谈高校管理中的激励技术

在高校的管理过程中，科学地选择激励技术是调动教职工积极性，发挥教职工创造性，质量和办学水平的有效的一从六个方面对此了探讨。     

全面提高农林院校硕士生计算机应用水平

随着我国改革开放步伐的加快、加入世贸组织日期的临近，高等农林院校硕士研究生的计算机教育将面临更大的挑战和机遇。如何抓住机遇，迎接挑战，全面提高农林院校硕士研究生计算机应用水平，是目前农林院校硕士生教育急需解决的问题之一。本在调查研究的基础上分析探讨了目前国内农林院校硕士研究生计算机教育存在的问题，并给出了几点改革建议。     

基于IL-HMMs预测模型的地下水埋深预测研究

以西北干旱典型县域磴口县为研究区,基于增量学习的改进隐马尔可夫预测模型(IL-HMMs),对区域地下水埋深进行了预测研究。为检验IL-HMMs模型预测效果,将模型预测结果与2013年长观井的实测数据进行了比较;同时为检验模型的优劣性,与未经增量学习的隐马尔可夫模型(HMMs)、加权马尔可夫链(WMCP)和BP神经网络(BP neural network,BPNN)预测模型的预测结果进行了比较。结果表明:与其他几种预测模型相比,IL-HMMs模型预测精度显著提高,误差更小,有较好的鲁棒性。并使用IL-HMMs模型对2018年地下水埋深进行了预测,预测结果表明,2018年地下水年平均埋深略有增加、局部区域地下水埋深增量加剧。基于IL-HMMs模型的地下水埋深预测具有很好稳定性的同时对新数据加入又有很好的鲁棒性,可为地下水埋深动态预测提供思路与方法补充,为区域地下水资源开发利用和保护提供重要依据。     

Role of social networks in urban forest management collaboration: A case study in northern Japan

Public participation is crucial for sustainable forest management. In particular, in urban forest areas, it is an important tool for overcoming conflicts among diverse needs regarding the forests through collaboration between citizens and governments. Such collaboration requires social learning. Social learning is dependent upon the presence of social networks that serve as an infrastructure for social capital. This study analyses the role of the social network in a participatory forest management approach of the Nopporo Forest Regeneration Project (NFRP) in the urban Nopporo National Forest in Hokkaido, northern Japan, aimed at restoring a typhoon damaged forest.Within the framework of the participatory approach the project hascreated a network of several citizen organizations for exchanging information. Outside this formal NFRP network several additional citizenorganizations are concerned about the Nopporo Forest management. The article describes the overall social network that has evolved around the Nopporo Forest and compares the attitudes and evaluations of the NFRP network organizations and the not formally NFRP related organizations towards their collaboration with government agencies and other citizen organizations. The overall social network around the Nopporo Forest had a multi-nodal character with the National Forest Agency and Hokkaido Prefectural Government acting as main central nodes. Only a few citizen organizations had direct relations to both central nodes; many organizations had links to either the National Forest Agency or the Prefectural Government. The organizations involved in the formal NFRP network had close ties with the National Forest Agency. This contributed to a positive evaluation of present forest management approach and the collaborative activities of the government agencies. In contrast, the organizations that were not involved in the formal NFRP network were found to have fewer ties with the National Forest Agency. The lack of opportunity to form a direct social learning relation hindered the formation of social capital and resulted in a lower evaluation of the participatory management approach as well as of the collaborative activities. Thus, although the participatory forest management approach of establishing formal social networks enhanced collaboration between the National Forest Agency and several citizen organizations and social learning, it was less successful in encouraging a democratic process involving all interested citizen organizations.