PSO-based single multiplicative neuron model for time series prediction

Single multiplicative neuron model is a novel neural network model introduced recently, which has been used for time series prediction and function approximation. The model is based on a polynomial architecture that is the product of linear functions in different dimensions of the space. Particle swarm optimization (PSO), a global optimization method, is proposed to train the single neuron model in this paper. An improved version of the original PSO, cooperative random learning particle swarm optimization (CRPSO), is put forward to enhance the performance of the conventional PSO. The proposed CRPSO, PSO, back-propagation algorithm and genetic algorithm are employed to train the model for three well-known time series prediction problems. The experimental results demonstrate the superiority of CRPSO-based neuron model in efficiency and robustness over the other three algorithms.     

Identification of relationship between sunspots and natural runoff in the Yellow River based on discrete wavelet analysis

Annual natural runoff is an important index of a river, which may be affected by solar activities. In this study, 304 years of annual natural runoff at the Sanmenxia station located in the Yellow River and the sunspot relative number are decomposed with the application of a Complex Morlet. According to the results of real part, modulus and second power of modulus, the annual runoff series at the Sanmenxia station has an obvious periodic oscillation on 90–100, 50–80, 35–50, 15–35, about 10, and less than 10-year scales. Also, there are obvious periodic variability with 60–90 years, 30–50 years and about 10 years. There are two centers of energy: one is about 1840–1850 on 7–11-year scale and the other is about 1825–1925 on 60–70-year scale. From the wavelet variance, 3, 26, 46, 68 year periods are detected within a 100-year scale, and the 68-year period is the most significant. Similar analyses are conducted for the sunspot relative number within the same period 1700–2003. The sunspot series shows 11- and 60-year period variation, as well as eight energy centers. Then, the correlation analyses for 11- and 60-year serial scales are computed. From a long-term period (1700–2003) view, there is no notable correlation between the natural runoff and the sunspot relative number; however, it is evident that the correlations exist within a short-term period. The results also indicate that the relationships between solar activities and the natural runoff in the Yellow River are complicated.     

GNSS-R信号反演土壤水分研究分析

由于GNSS-R信号具有全天候、穿透性以及不受云的影响,且对土壤水分非常敏感等特性,使其在遥感研究全球变化中具有独特的优势。简要评述了利用GPS地面反射信号在土壤水分反演研究领域的进展,然后侧重分析介绍了GPS反射信号土壤水分反演原理,前向模型分析反演土壤水分的关键技术,并指出目前存在的问题和发展方向。     

The application of a binary division procedure to the classification of forest subcategories using MODIS time-series data during 2000–2010 in China

Forests account for more than 23% of China’s total area. As the most important terrestrial ecosystem, forests have tremendous ecological value. However, it remains difficult to classify forest subcategories at the national scale. In this study, a newly developed binary division procedure was used to categorize forest areas, including their spatiotemporal dynamics, during the period 2000–2010. Time-series images acquired using the Moderate Resolution Imaging Spectroradiometer (MODIS), together with auxiliary data on land use, climate zoning, and topography, were utilized. Hierarchical classification and zoning were combined with remote-sensing auto-classification. Based on the forest extent mask, the state-level forest system was divided into four classes and 18 subcategories. The method achieved an acceptable overall accuracy of 73.1%, based on a comparison to the sample points of China’s fourth forest general survey data set. In 2010, the total forest area was 1.755 × 10⁶ km², and the total area of and shrubs was 4.885 × 10⁵ km². The total area of woodland increased by 2536.25 km² during the decade 2000–2010. The shrub subcategories exhibited almost no change during this time period; however, significant changes in forest area occurred in the mountainous region of Northeast China as well as in the hilly regions of Southern China. The main transformations took place in cold-temperate and temperate mountainous deciduous coniferous forest, subtropical deciduous coniferous forest, subtropical evergreen coniferous forest, and temperate and subtropical deciduous broadleaved mixed forests. The binary division procedure proposed herein can be used not only to rapidly classify more forest subcategories and monitor their dynamic changes, but also to improve the classification accuracy compared with global and national land-cover maps.     

Bridging rigorous assessment of water availability from field to catchment scale with a parsimonious agro-hydrological model

While simple crop and hydrological models are limited with respect to the number and accuracy of the processes they incorporate, complex models have high demand for data. Due to the limitations of both categories of models, there is a need for new agro-hydrological models that simulate both crop productivity and water availability in agricultural catchments, with low data and calibration requirements. This study aimed at developing a widely applicable parsimonious agro-hydrological model, AquaCrop-Hydro, which couples the AquaCrop crop water productivity model with a conceptual hydrological model. AquaCrop-Hydro, simulating crop productivity, the daily soil water balance and discharge at the catchment outlet, performed well for an agricultural catchment in Belgium. The model can be used to investigate the effect of agricultural management and environmental changes from field to catchment scale in support of sustainable water management in agricultural areas.     

Set-membership estimation from poor quality data sets: Modelling ammonia volatilisation in flooded rice systems

A set-membership (bounded-error) estimation approach can handle small and poor quality data sets as it does not require testing of statistical assumptions which is possible only with large informative data sets. Thus, set-membership estimation can be a good tool in the modelling of agri-environmental systems, which typically suffers from limited and poor quality observational data sets. The objectives of the paper are (i) to demonstrate how six parameters in an agri-environmental model, developed to estimate NH₃ volatilisation in flooded rice systems, were estimated based on two data sets using a set-membership approach, and (ii) to compare the set-membership approach with conventional non-linear least-squares methods. Results showed that the set-membership approach is efficient in retrieving feasible parameter-vectors compared with non-linear least-squares methods. The set of feasible parameter-vectors allows the formation of a dispersion matrix of which the eigenvalue decomposition reflects the parameter sensitivity in a region.     

Recursive projection twin support vector machine via within-class variance minimization

In this paper, a novel binary classifier coined projection twin support vector machine (PTSVM) is proposed. The idea is to seek two projection directions, one for each class, such that the projected samples of one class are well separated from those of the other class in its respective subspace. In order to further boost performance, a recursive algorithm for PTSVM is proposed to generate more than one projection axis for each class. To overcome the singularity problem, principal component analysis (PCA) is utilized to transform the data in the original space into a low-dimensional subspace wherein the optimization problem of PTSVM is convex and can be solved efficiently. The experimental results on several UCI benchmark data sets and USPS digit database show the feasibility and effectiveness of the proposed method.     

基于特征的面向对象虚拟GIS数据模型分析及其数据库实现*

从设计虚拟GIS数据模型应考虑的问题出发,提出一种全新的基于特征的面向对象虚拟GIS数据模型构建思路,并详细分析了其对象的结构;最后介绍基于该数据模型的数据库构建过程和步骤,为后续原型系统的开发提供数据支持。     

抗性淀粉测定方法的研究

抗性淀粉的测定方法有Berry法、Englys法、Bjorck法、Champ法、Goni法等.以木薯抗性淀粉和抗性淀粉标准品为原料,通过对抗性淀粉的处理方法(AOAC法、Goni法)以及还原糖的测定方法(3,5-二硝基水杨酸法、D-葡萄糖法)进行对比,得到木薯抗性淀粉最适合的测定方法.同时也研究了样品多少对测定结果的影响.结果表明,AOAC-GOPOD法操作简单、准确性高、重复性好,酶用量充足,是测定木薯抗性淀粉的首选方法.     

Hydrological Evolution of Wetland in Naoli River Basin and its Driving Mechanism

Naoli river basin(NRB), with an area of 24,863 km², is the largest basin and also the largest marsh distribution area in Sanjiang Plain, Heilongjiang, China. The hydrological evolution process of wetland in NRB has made a marked ecological responses for anthropic activities, also reflects the drying trend of the Sanjiang Plain, Northeast China. Global climate warming also contributes to the hydrological evolution process. The following key research results are obtained: (1) The monthly average water level of Naoli river at Caizuizi hydrological station in different ages showed a marked decline tendency, the annual mean water level dropped from 96.63 m during 1960–1969 to 95.59 m during 2000–2005, the water level drawdown is 1.04 m; (2) The annual runoff flowing into wetlands in NRB decreased. Duration of Naoli river and its tributaries being thoroughly frozen from riverbed to river-water-surface showed an prolonged trend, and the water level drawdown in frozen seasons increased. The water storage capacities of wetlands in NRB declined. (3) The interactions between ground water and surface water in wetland areas are close. The ground water level variation span is bigger than that of surface water level in wetland areas of NRB. The drawdown of ground water level promotes the surface water level to decline, correspondingly. In recent 20 years, the cultivated area extension of rice field in upstream NRB has made an adverse influence on the hydrological processes of wetlands. (4) The wetland area decrease and farmland area increase significantly contribute to the runoff depth decrease of wetlands in NRB. The runoff depth variability has been mostly posed by anthropic activities. (5) Reservoirs, ditches and dykes in NRB have greatly changed the runoff generation processes. Thickness of the seasonal frozen soil layer becoming thinner and the evaporation potential becoming bigger also contribute to the runoff depth reduction and the water level drawdown of rivers. The present study results will provide a scientific basic for developing an integrated watershed management program for NRB, especially, restoring the wetland hydrological processes, maintaining or improving the wetland structure and enhancing the wetland service functions.