悬沙的ADCP估测方法

ADCP估测悬沙含量是基于声波的背散射强度正比于悬沙浓度的理论。在实际测验中，由于多种因素干扰，ADCP所得到的背散射强度与悬沙浓度之间存在着不定的非线性关系。同传统的回归方法比较，BP网络模型方法可以使含沙估测精度有较大的提高。     

Neural networks for wave forecasting

The physical process of generation of waves by wind is extremely complex, uncertain and not yet fully understood. Despite a variety of deterministic models presented to predict the heights and periods of waves from the characteristics of the generating wind, a large scope still exists to improve on the existing models or to provide alternatives to them. This paper explores the possibility of employing the relatively recent technique of neural networks for this purpose. A simple 3-layered feed forward type of network is developed to obtain the output of significant wave heights and average wave periods from the input of generating wind speeds. The network is trained with different algorithms and using three sets of data. The results show that an appropriately trained network could provide satisfactory results in open wider areas, in deep water and also when the sampling and prediction interval is large, such as a week. A proper choice of training patterns is found to be crucial in achieving adequate training.     

分形城市研究进展：从几何形态到网络关联

城市是人类文明最主要的聚集地,也是一个开放复杂演化巨系统,认识其空间复杂性成为城市科学研究的热点和前沿。城市研究正呈现“从位置和场所向关联和流,从物质空间向城市网络空间”的转向。人类对城市的认识也从“空间是机器”转向“城市有机生命体”。分形是大自然的语言和地理学第四代语言,是挖掘城市空间自组织规律的有效工具,在揭示城市有机体复杂演化机制方面发挥重要作用。目前分形城市研究以指标构建和实证分析为主,缺乏系统的梳理和回顾;内容上侧重几何分形,复杂城市网络视角下的结构分形研究薄弱。本文简要回顾了近30余年来分形城市研究的发展历程,梳理了分形城市研究脉络：从城市形态的几何分形到城市结构与关联的网络分形,从静态分形特征到动态异速生长,并展望了分形城市未来研究方向。     

Discussion on “Correction of soil parameters in calculation of embankment settlement using a BP network back-analysis model” By Zhi-liang Wang, Yong-chi Li, R.F. Shen [Engineering Geology 91 (2007) 168–177]

The paper studied by Yong-chi Li and R.F. Shen (2007) includes some problems regarding the application of the proposed Neural Network (NN) approach. A very limited number of data has been used as testing set (only 3 among 52 data sets) which should be 20–30% of the database. The NN application in the study is not a function approximation problem where same input must always lead to the same output. NNs cannot be used for such an application. Moreover the generalization capability of the NN model has not been investigated. This discussion, aims to points out controversial points of the paper.     

基于模糊神经网络的模糊空间对象生成方法研究

随着对GIS中的空间对象模型和自然地理特征表达的研究深入,模糊空间对象被提出。针对模糊空间对象表达的特点,提出了一种基于模糊神经网络的模糊空间对象生成方法。该方法将模糊技术与神经网络相结合,利用神经网络的学习能力调整模糊隶属函数和模糊规则,使系统具备自适应的特性。实验表明,这种基于模糊神经网络的生成模糊空间对象的方法比传统方法大大的提高了成果的精度。     

Transformative Research in Geography Education: The Role of a Research Coordination Network

This article considers the concept and significance of transformative research in the context of geography education. It provides an overview of how the capacity-building activities and management operations of a research coordination network (RCN) are designed to support broad-scale advances in geography education theory, methods, and practice. Vignettes of RCN activities are presented as examples of pathways toward transformative research in the areas of geography learning progressions, assessments of spatial thinking, and geospatially enabled project-based learning. Beyond the prospect of introducing new paradigms of learning and using research findings to inform and systematically change approaches to teacher education and curriculum development, an RCN offers an opportunity to plan broad-based strategy and develop leadership needed to address many long-standing challenges that have undermined the quality and quantity of geography education research. These challenges include the low visibility of geography education research relative to other geographic subdomains, the difficulty of carrying out interdisciplinary and international research collaborations, low rates of transfer and uptake of research findings in practitioner communities and in policymaking, and the erosion of graduate-level programs that prepare students to plan and design conceptually rigorous educational research in geography.     

Interactive Videos Enhance Learning about Socio-Ecological Systems

Two forms of interactive video were assessed in an online course focused on conservation. The hypothesis was that interactive video enhances student perceptions about learning and improves mental models of social-ecological systems. Results showed that students reported greater learning and attitudes toward the subject following interactive video. Moreover, metrics of network complexity applied to students' concept maps of socio-ecological systems increased longitudinally through the course highlighting greater awareness of socio-ecological linkages. We conclude that interactive video can increase awareness of interdisciplinary connections in socio-ecological systems and should be more widely employed in general education geography courses.     

Social mix revisited: within- and across-neighborhood ties between ethnic minorities of differing socioeconomic backgrounds

Creating social mix in neighborhoods has been an important urban policy during the past years. The aim is the development of category-crossing ties between the middle and lower classes. However, studies found little evidence of such ties. This paper identifies two reasons why this might be the case. First, studies usually analyze the resource flow from native middle classes to disadvantaged residents. Second, the resource flow is analyzed within one neighborhood only. Based on interviews and network analysis with second generation, upwardly mobile Turkish-Germans in Berlin, I show that they act as cultural and language brokers, benefiting lower class co-ethnics. They provide exactly the information and resources to people with a lower class background that are envisioned by social mixing programs. Moreover, the resource flow occurs within but also across neighborhoods, whereby ‘second neighborhoods’ such as the previous neighborhood or the neighborhood where the workplace is located are particularly important.     

An Investigation of the Role of Social Dynamics in Conversion to Sustainable Integrated Mangrove‐Shrimp Farming in Ben Tre Province,Vietnam

In the coastal area of the Vietnamese Mekong Delta, much of the mangrove forest has been cut to make space for expansion of industry and aquaculture. Export‐oriented shrimp farming is a particularly fast‐growing business. Nonetheless, the importance of tropical mangrove forest ecosystems for coastal protection and marine biodiversity is widely recognized. The Vietnamese government, supported by non‐governmental organizations and donors, has sought to restore mangrove forest. To this end, the government has promoted mixed or integrated mangrove‐shrimp systems in which farmers maintain at least 40 per cent of their area under mangrove cover. Since 2012, mangrove reforestation, care and protection has benefited from local authority stimulus as well. Multiple studies have examined the condition of the mangrove forest in Ben Tre and other coastal provinces of the Mekong Delta. However, no research has investigated the role of social dynamics in farmers’ willingness to shift to, or maintain, integrated mangrove‐shrimp systems. Specifically, the influence of information, group dynamics and social learning on farmer decision‐making is poorly understood and, indeed, hardly investigated in Vietnam. This article reports on a study of social processes in three communes in Binh Dai District, Ben Tre Province, Vietnam. We conducted 42 semi‐structured interviews (with 34 farmers and eight local officials) and used secondary data. Our preliminary findings indicate that social dynamics in these communes were issue‐driven and played an important role in farmers’ decisions to adopt, or convert to, the integrated mangrove‐shrimp farming system. Television, radio, the internet, books, neighbours and training courses all had some influence in farmer decision‐making processes. However, our findings suggest that the accessibility, usefulness, relevance and approach of these communication methods must be improved if they are to adequately inform and support local farmers.