专家系统及其在矿产预测中的应用

专家系统是一门新兴的计算机人工智能实用学科，它能够应用专家的知识和思维方式去解决实际问题。它主要由知识库和推理机组成。ＨＮＤＰＥＳ系统是在总结河南主要矿产成矿规律的基础上建造的矿床预测专家系统。在河南省富铝土矿成矿预测中取得了良好的效果。     

A practical solution for linear inference computations

Summary. In this paper, we present a matrix form of Backus' theory of linear inference with multiple predictions. The Bayesian approach used by Backus allows the treatment of erroneous data and the imposition of the essential a priori bound on the model norm. We introduce a modification which involves translating the problem in accordance with an estimated model. Such a model may be known a priori or it may be constructed from the data. We are effectively able to bound the norm of all acceptable models from above and below and this results in more confining estimates of the predictions than provided by just an upper bound. In addition, the model construction approach allows us to make maximum use of the data in the inference computation. Our algorithm is robust and efficient, and estimates comparable to to those obtained from linear programming techniques have been achieved.     

Artificial intelligence methods in geological forecasting

The objective of applications of expert systems to geological forecasting is to use heuristic knowledge of experienced geologists, as well as their intuition and facility for drawing the right forecast conclusions based on incomplete data. At the same time, considerable experience is accumulated in geological forecasting with formal mathematical models that generalize the setting of some forecast problem classes. Thus, the bottom-up heuristic approach and the more formal top-down methods are aspiring to the same aim, so they supplement and strengthen each other. A forecast expert system called GENESIS that allows both approaches to be used has been produced. The heuristic part of GENESIS is the empty expert system, which consists of the knowledge definition language, destined for an expert geologist, the knowledge base used for forecast models storing, then forming knowledge base facilities, relational database for storing user's data and forecast specimen, components that organize the certain inference and its explanation.     

POPULATIONS,SAMPLES AND STATISTICAL INFERENCE IN GEOGRAPHY

This paper questions the validity and relevance of the application of procedures of classical statistical inference to population data in geography. Arguments for such procedures include the notions of temporal and spatial samples, measurement error, modifiable areal units, data vetting and stochastic processes. It is concluded that such arguments cannot be justified in terms of statistical theory.     

Inferring trip purposes and uncovering travel patterns from taxi trajectory data

Global positioning system-enabled vehicles provide an efficient way to obtain large quantities of movement data for individuals. However, the raw data usually lack activity information, which is highly valuable for a range of applications and services. This study provides a novel and practical framework for inferring the trip purposes of taxi passengers such that the semantics of taxi trajectory data can be enriched. The probability of points of interest to be visited is modeled by Bayes’ rules, which take both spatial and temporal constraints into consideration. Combining this approach with Monte Carlo simulations, we conduct a study on Shanghai taxi trajectory data. Our results closely approximate the residents’ travel survey data in Shanghai. Furthermore, we reveal the spatiotemporal characteristics of nine daily activity types based on inference results, including their temporal regularities, spatial dynamics, and distributions of trip lengths and directions. In the era of big data, we encounter the dilemma of “trajectory data rich but activity information poor” when investigating human movements from various data sources. This study presents a promising step toward mining abundant activity information from individuals’ trajectories.     

Modelling the influence of environmental and weather factors on the density of the invasive polychaete Boccardia proboscidea

The inter‐tidal zone around sewage discharges in a Southwest Atlantic shore (Mar del Plata, Argentina) is currently colonized by extensive inter‐tidal reefs of the invasive spionid Boccardia proboscidea. Understanding the links between both human and natural disturbances and the massive development of non‐indigenous species will help prevent marine bioinvasions, which are already favoured by global oceanic trade. We present herein predictive models for variations in the density of B. proboscidea around sewage discharges of Mar del Plata, using environmental (pH, turbidity, temperature, salinity and total organic matter content), weather (wind direction and storm records), spatial (sites) and temporal (season and year) variables. Density variations were modelled by generalized linear models, and model averaging (multimodel inference) was used to obtain predicted values. The highest predicted values of B. proboscidea density occurred at sites to the south of the sewage effluent in spring. These sites are more affected by urban effluent discharges and they showed increased B. proboscidea density when the north wind was predominant. In addition, B. proboscidea density values were higher in sites with 20–22 °C (seawater temperature), high total organic matter content in sediments and low salinity. The averaged model was only a good ‘predictive model’ for sites to the north of the outfall, but was useful as an ‘explanatory model’ in all sites. Such predictions may help to back up conservation and management policies and decisions.     

圆弧破坏边坡反演设计的ANN方法与ANFIS方法的比较研究

圆弧破坏边坡反演设计方法,是根据边坡的岩土力学参数及边坡高度,在确保安全系数满足要求的前提下,对圆弧破坏边坡的边坡角进行设计的一种新方法。建立圆弧破坏边坡反演设计方法的关键,就是要对大量稳定圆弧破坏边坡实例加以集成,以建立从{ , c, , H, F}到 的映射。文中收集了大量稳定圆弧破坏边坡实例,采用ANN和ANFIS对其进行了集成,分别建立了圆弧破坏边坡反演设计的ANN方法和ANFIS方法,进而又采用圆弧破坏边坡实例对两者的反演结果进行了比较。结果表明,ANFIS更适合于用来建立圆弧破坏边坡反演设计方法。     

Delineation of hydrologically similar units in a watershed based on fuzzy classification of soil hydraulic properties

Evaluation of flow and transport processes in a watershed‐scale requires that the watershed be divided into homogenous spatial units referred to as hydrologically similar units (HSUs). Although a few discretization schemes are already in use, a universally acceptable method of obtaining HSUs is yet to emerge. In this study, we developed a fuzzy inference system (FIS) to classify the saturated hydraulic conductivity (K_s) and two water‐retention parameters α and n into fuzzy logic‐based soil hydrologic classes (FSHCs). Analysis of these classes showed that soil properties within an FSHC have less variability and those between two FSHCs have large variability. This result suggested that soils belonging to a specific FSHC may be more similar than those across different FSHCs and may be grouped together to represent an HSU. Soils within a specific hydrologic class were aggregated to delineate HSUs within the watershed. For the Dengei Pahad micro‐watershed (DPW), this approach showed five distinct regions representing a discretized zone having similar soil hydraulic properties. Application of this approach on a larger international database of soil hydraulic properties revealed that the developed hydrologic classes are quite comparable across different databases. The delineated HSUs based on these FSHCs were also better than the soil series map of the watershed in maintaining the soil heterogeneity of the watershed. Moreover, this new discretization scheme using the SWAT modelling environment showed better performance than the soil series‐based discretization approach. Copyright © 2010 John Wiley & Sons, Ltd.