The Relationship between Decision Trees and the Scale of Train Data Set

Decision Trees need train samples in the train data set to get classification rules. If the number of train data was too small, the important information might be missed and thus the model could not explain the classification rules of data. While it is not affirmative that large scale of train data set can get well model. This Paper analysis the relationship between decision trees and the train data scale. We use nine decision tree algorithms to experiment the accuracy, complexity and robustness of decision tree algorithms. Some results are demonstrated.

Compact Reconfigurable Binary-Decision-Diagram Logic Circuit on a GaAs Nanowire Network

We describe a reconfigurable binary-decision-diagram logic circuit based on Shannon's expansion of Boolean logic function and its graphical representation on a semiconductor nanowire network. The circuit is reconfigured by using programmable switches that electrically connect and disconnect a small number of branches. This circuit has a compact structure with a small number of devices compared with the conventional look-up table architecture. A variable Boolean logic circuit was fabricated on an etched GaAs nanowire network having hexagonal topology with Schottky wrap gates and SiN-based programmable switches, and its correct logic operation together with dynamic reconfiguration was demonstrated.

An automata theoretic decision procedure for the propositional mu-calculus

The propositional mu-calculus is a propositional logic of programs which incorporates a least fixpoint operator and subsumes the propositional dynamic logic of Fischer and Ladner, the infinite looping construct of Streett, and the game logic of Parikh. We give an elementary time decision procedure, using a reduction to the emptiness problem for automata on infinite trees. A small model theorem is obtained as a corollary.

黄土高原降雨径流调控利用潜力定量评价模型

降雨径流的调控利用是缓解黄土高原干旱缺水与控制水土流失的有效手段,研究区域降雨径流调控利用潜力的定量评价对黄土高原降雨径流合理利用的宏观决策与规划设计具有重要意义。以黄土高原为例,将可以调控利用的最大降雨径流量作为资源化潜力值,从宏观尺度上,系统分析了影响该潜力的各个因素,确定出黄土高原降雨径流调控利用潜力的各项评价指标,利用GIS技术,建立了降雨径流各个影响因素的专题图层,提取出各个影响因素专题信息。在上述基础上,引入人工神经网络建模方法,建立了黄土高原降雨径流调控利用潜力BP网络模型,并利用实际资料对网络模型进行了训练和预测,取得了较好的结果。评价模型可供黄土高原降雨径流调控利用及其生态与环境保护工作参考。

Decision tree classification of land cover from remotely sensed data

Decision tree classification algorithms have significant potential for land cover mapping problems and have not been tested in detail by the remote sensing community relative to more conventional pattern recognition techniques such as maximum likelihood classification. In this paper, we present several types of decision tree classification algorithms arid evaluate them on three different remote sensing data sets. The decision tree classification algorithms tested include an univariate decision tree, a multivariate decision tree, and a hybrid decision tree capable of including several different types of classification algorithms within a single decision tree structure. Classification accuracies produced by each of these decision tree algorithms are compared with both maximum likelihood and linear discriminant function classifiers. Results from this analysis show that the decision tree algorithms consistently outperform the maximum likelihood and linear discriminant function classifiers in regard to classf — cation accuracy. In particular, the hybrid tree consistently produced the highest classification accuracies for the data sets tested. More generally, the results from this work show that decision trees have several advantages for remote sensing applications by virtue of their relatively simple, explicit, and intuitive classification structure. Further, decision tree algorithms are strictly nonparametric and, therefore, make no assumptions regarding the distribution of input data, and are flexible and robust with respect to nonlinear and noisy relations among input features and class labels.

基于GIS的区域水土流失评价模型

区域水土流失评价对于水土流失区域治理的宏观决策、规划等具有十分重要的意义 .本文以黄土高原地区为例 ,结合影响水土流失的各个因子 ,分析了该区的自然特征 ,确定了进行区域水土流失评价的各项指标 (模型参数 ) ,并运用 GIS,集成了多种来源、多种比尺和多种类型的数据 ,建立了该区的水土流失宏观定量评价模型

基于RS和GIS的区域水土流失快速定量评价方法

区域水土流失的快速调查和评价对于水土保持宏观决策、灾情快速反应以及水土流失定期公告制的建立具有十分重要的意义。立足于区域水土流失问题的探索和 3S技术应用的研究 ,提出了区域水土流失宏观快速定量评价的方法及其实现的技术路线 ,并以整个黄土高原为研究区进行了实例研究 ,确定了一套适于该区水土流失宏观定量评价的指标 ,建立了相应的评价模型 ,并利用该模型对研究区一定年限内的水土流失状况进行了评价 ,获得了令人满意的结果

Amplified electrochemical aptasensor taking AuNPs based sandwich sensing platform as a model

Here, we report a sensitive amplified electrochemical impedimetric aptasensor for thrombin, a kind of serine protease that plays important role in thrombosis and haemostasis. For improving detection sensitivity, a sandwich sensing platform is fabricated, in which the thiolated aptamers are firstly immobilized on a gold substrate to capture the thrombin molecules, and then the aptamer functionalized Au nanoparticles (AuNPs) are used to amplify the impedimetric signals.

An application of the analytic hierarchy process and fuzzy logic inference in a decision support system for forage selection

Forage selection plays a prominent role in the process of returning cultivated lands back into grasslands. The conventional method of selecting forage species can only provide attempts for problem-solving without considering the relationships among the decision factors globally. Therefore, this study is dedicated to developing a decision support system to help farmers correctly select suitable forage species for the target sites. After collecting data through a field study, we developed this decision support system. It consists of three steps: (1) the analytic hierarchy process (AHP), (2) weights determination, and (3) decision making. In the first step, six factors influencing forage growth were selected by reviewing the related references and by interviewing experts. Then a fuzzy matrix was devised to determine the weight of each factor in the second step. Finally, a gradual alternative decision support system was created to help farmers choose suitable forage species for their lands in the third step. The results showed that the AHP and fuzzy logic are useful for forage selection decision making, and the proposed system can provide accurate results in a certain area (Gansu Province) of China.

大城市内部商业环境满意度评价与消费区位决策研究-以北京市西城区和海淀区为例

Since 1990s, commercial conditions in China including commercial environment, retail types, scale of retail enterprises, spatial structure of retail and shopping decision making factors have changed. In order to keep up with these changes, commercial geography should set up new perspectives, theories and methods to analyze its internal mechanism and changing rules, and thus provide reasonable and practical scientific basis to commercial planning, location decision of retail enterprises and commercial environment construction. Taking Xicheng and Haidian District of Beijing as research case, which is a sector region from city center to rural region, this paper selects 12 commercial centers as most important study objects of this sector. This paper mainly makes use of the methods of Modeling, Pearson Bivaiiate Correlations Analysis, Factor Analysis and Logit model. Based on 1300 questionnaires and fieldwork, this paper focuses on modeling of Consumer Satisfaction of Commercial Environment (CSCE), evaluation of commercial environment and driving factors of consumers' shopping location decision. Firstly, this paper discusses the development of commercial geography and commercial environment evaluation, the new characteristics and trends of commercial development in Beijing and physical commercial environment of Xicheng and Haidian District of Beijing from chapter 1 to chapter 4. Secondly, this paper summarizes characteristics of residents' shopping behavior in chapter 5. Thirdly, this paper sets up an evaluative model of CSCE, and analyzes consumer satisfaction indexes of commercial environment and their spatial features in chapter 6. Fourthly, this paper infers how residents' attributes and shopping behaviors affect their preferences of shopping location and what are residents' shopping location decisions and their influencing factors in chapter 7. Fifthly, this paper constructs a significant index model and a pyramidal framework of CSCE, and further analyzes the diversity and competitive advantage of commercial environment in chapter 8. Finally, some conclusions are drawn as follows: 1. Characteristics of residents' shopping behavior mostly embody residents' time distance preference, commodity consumption preference, shopping time distribution and shopping activity characteristics. The important factors that influence shopping location choice of residents are distance, transportation, commodity price, commodity types and commodity quality. However, the important factors, which influence shopping location re-choice of residents, are commodity price, commodity quality, commodity types and transportation. 2. CSCE indexes of 12 commercial centers show us significant spatial characteristics, such as spatial differences of "Center-fringe region", spatial characteristics of axes, spatial diversity of ring roads and so on. 3. Influencing factors including factor endowments, relative establishment factor and location and transportation factor of commercial environment are of importance for CSCE. 4. Logit model 1 indicates that shopping behavior of residents is significantly and positively related to working in high-tech companies, high income and by car and positively related to high school diploma, by bus and subway. 5. Logit model 2 indicates that residents' shopping location decision is significantly and positively related to leisure establishment and relative restaurant and entertainment establishment and negatively related to commercial location, commodity price, service quality, parking site. 6. The significant index model and the pyramidal framework of CSCE indicate competitive advantages are crucial to attractive capability of commercial center, and competitive weakness limits development of commercial centers, in particular the weakness of service quality and parking site now is the chief factors restricting development of commercial centers

民众社会风险认知的影响因素及作用机制

Risk perception is one of important subjects in management psychology and cognitive psychology. It is of great value in the theory and practice to investigate the social risk events that the public cares a lot especially in this social transition period. Furthermore, this study explored the factors that influence the risk perception and the results caused by risk perception. A survey including 30 hazards and 8 risk attributes was designed and distributed to about 3, 200 residents of 8 districts, Beijing. The major findings are listed as following： Firstly, combining the methods of system science and psychology, GAE program was used to indentify 7 groups of social risk events, such as national safe, government management, social stability, general mood of society, economic and finance, resources and environment & daily life problems. This study provided substance for the following studies and it was also a new attempt in research method which is of certain reference value for the related researches. Secondly, a scale of societal risk perception was designed and 2 factors were identified (Dread Risk & Unknown Risk). Reliability analysis, EFA and CFA show the reliability and validity of the societal risk questionnaire is good enough. The investigation using this scale showed that older participants and higher socioeconomic status perceived the societal hazards to be more threatening than did younger participants and lower socioeconomic status. However, there is no gender difference. Thirdly, structural equation model was used to analyze the influence factors and mechanism of societal risk perception. Risk taking, government support and social justice could influence societal risk perception directly. Government support moderated the relationship between government trust and societal risk perception. Societal risk perception influenced life satisfaction, public policy preferences and social development belief. Multi-group analysis was used to find out that the participants who have different socioeconomic status express different mechanism. Fourthly, the result of the research was used to explore the risk event of 2008 Olympic game. The results showed that government support and preparation of Olympic game influenced societal risk perception directly. Preparation moderated the relationship between government trust and risk perception. Risk perception influenced worry, effect of Olympic game and belief of successl. This result proved that risk perception could be used as an indicator. The indictor of risk perception was used to identify the characteristics of higher risk perception group. Finally, suggestions to the related decision were provide to the government.