Adaptive neuro-fuzzy inference system for prediction of water level in reservoir

Accurate prediction of the water level in a reservoir is crucial to optimizing the management of water resources. A neuro-fuzzy hybrid approach was used to construct a water level forecasting system during flood periods. In particular, we used the adaptive network-based fuzzy inference system (ANFIS) to build a prediction model for reservoir management. To illustrate the applicability and capability of the ANFIS, the Shihmen reservoir, Taiwan, was used as a case study. A large number (132) of typhoon and heavy rainfall events with 8640 hourly data sets collected in past 31 years were used. To investigate whether this neuro-fuzzy model can be cleverer (accurate) if human knowledge, i.e. current reservoir operation outflow, is provided, we developed two ANFIS models: one with human decision as input, another without. The results demonstrate that the ANFIS can be applied successfully and provide high accuracy and reliability for reservoir water level forecasting in the next three hours. Furthermore, the model with human decision as input variable has consistently superior performance with regard to all used indexes than the model without this input.     

基于知识与规则的城市管线数据计算机监理校验

本文通过对城市管线数据的分析与处理，得到对城市管线数据进行计算机监理校验的知识与规则，并利用这些知识与规则进行综合的城市管线数据校验。     

地下水管理模型研究进展

本文在分析和总结前人研究成果的基础上,将地下水管理模型的研究过程划分为两大阶段:模型理论探索到推广应用阶段(1970~1990年)和模型实用性研究阶段(1990年至今)。在对各阶段的研究内容以及存在问题等进行概述的基础上,指出建立地下水资源管理的多目标动态规划模型将是未来地下水管理模型的发展方向和趋势,但需要采用更为先进的优化算法对其进行求解,同时对地下水管理模型与GIS技术的集成进行了展望。     

海上爆炸排淤填石陆上装药机具的研制与施工方法

介绍了海上爆炸排淤填石陆上装药机具的主要结构特点、参数和构造以及陆上装药施工方法。     

Failure Process after Peak Strength of Artificial Joints by Fractal Dimension

Because lack of information when the joints exhibit strain softening behavior, the transition from peak to residual values is assumed to decrease either linearly or exponentially. Also, displacement of slide side after peak is much larger than the peak displacement and the stress approaches the residual state, thus studying failure process after peak strength is very important. In this research, three types of artificial joints with tooth-shaped asperity under repeated direct-shear were tested. Continuously movement of slide side after peak strength was monitored during shearing test. Reduction of shear parameters was examined according to two failure criteria (Barton and Patton). JRC value (Joint Roughness Coefficient) for a given profile was estimated by fractal dimension. One of the results of this study is that Barton’s criterion predicts a good estimation of residual strength and the second result is when the amount of fractal dimension of a joint surface increases, the JRC amount also increases, and with having value of h (height average) and l (base average) of a tooth-shaped asperity can determine the JRC of joint surface. M. Askari is a M.Sc Student of Engineering Faculty, Mining Engineering Department, Tarbiat Modares University, Tehran.     

Development and application of reservoir models and artificial neural networks for optimizing ventilation air requirements in development mining of coal seams

In longwall development mining of coal seams, planning, optimizing and providing adequate ventilation are very important steps to eliminate the accumulation of explosive methane–air mixtures in the working environment. Mine operators usually try to supply maximum ventilation air based on the capacity of the system and the predicted need underground. This approach is neither economical nor safer as ventilation capacity may decrease in time depending on various mining and coalbed parameters. Thus, it is important to develop better engineered approaches to optimize mine ventilation effectiveness and, therefore, to ensure a safer work environment.This study presents an approach using coalbed methane reservoir modeling and an artificial neural network (ANN) design for prediction and optimization of methane inflows and ventilation air requirements to maintain methane concentrations below statutory limits. A coalbed reservoir model of a three-entry development section, which is typical of Pittsburgh Coalbed mines in the Southwestern Pennsylvania section of Northern Appalachian Basin, was developed taking into account the presence and absence of shielding boreholes around the entries against methane inflow. In the model, grids were dynamically controlled to simulate the advance of mining for parametric simulations.Development and application of artificial neural networks as an optimization tool for ventilation requirements are introduced. Model predictions are used to develop, train, and test artificial neural networks to optimize ventilation requirements. The sensitivity and applications of proposed networks for predicting simulator data are presented and discussed. Results show that reservoir simulations and integrated ANN models can be practical and powerful tools for predicting methane emissions and optimization of ventilation air requirements.     

Artificial tracers for geothermal reservoir studies

Safe disposal of thermally spent geothermal brines that contain environmentally hazardous constituents is commonly obtained by reinjection. The reinjection process also serves to maintain reservoir pressure, enhance thermal recovery, and eliminate possible compactional subsidence. To avoid premature thermal breakthrough of reinjected fluids, tracer tests are employed for detection and evaluation of preferential path networks. In this paper some promising tracers that have not received much attention in geothermal reservoir studies are discussed, and a comprehensive tabulation of field sites of artificial tracer utilization is presented. Chemical and transport processes responsible for tracer retention by the formation of reservoir solids, as well as available tracer detection techniques, are emphasized.     

Integrating GIS and DSS for identification of suitable areas for artificial recharge,case study Meimeh Basin,Isfahan, Iran

Flood spreading is an inexpensive method for flood mitigation and artificial recharge of aquifers that results in a large budget return for relatively small investment.It is necessary to study some regional characteristics in order to determine the appropriate areas for artificial groundwater recharge by flood spreading in Meimeh Basin, Isfahan Province, Iran. Necessary regional characteristics to be studied are: slope, infiltration rate, sediment thickness, transmissivity, and water quality. In this research to identify suitable areas for artificial recharge several thematic layers were prepared, assigning each layer to one of the mentioned characteristics. The thematic layers were classified to several classes based on the existing criteria. All of the classes of the thematic layers were integrated and analyzed using a decision support system (DSS) in a geographical information system (GIS) environment. Finally suitability of the integrated classes for artificial recharge was identified in which the following classes were separated:(i) Very suitable, (ii) suitable, (iii) moderate suitability, and (iv) unsuitable.The validity of the generated model was verified by applying the model to a number of successful floodwater spreading stations throughout Iran. The verified model showed satisfactory results for all of the stations. The results for Meimeh Basin showed that about 70% of the Quaternary sediments in the studied area are suitable and moderately suitable for artificial recharge by flood spreading.     

U.K.USAGE OF CHEMOMETRICS AND ARTIFICIAL INTELLIGENCE IN QSAR ANALYSIS

A survey of members of the U.K.QSAR Discussion Group has been made to determine the extent ofuse and development of chemometric and artificial intelligence(AI)methods in the analysis ofmultivariate quantitative structure-activity relationship(QSAR)data in the U.K.Chemometric methodswere found to be well established in both industrial and educational establishments and there wassignificant method development occurring.AI methods were not employed to any great extent and thegeneral level of interest in these techniques was low compared to chemometric methods.A requirementfor more education in multivariate statistical methods and regression methods was indicated.A need fora user-friendly,comprehensive,commercially available multivariate statistical package containingmultivariate stability testing and regression diagnostic methods was identified.     

Canonical elements and Keplerian-like solutions for intermediary orbits of satellites of an oblate planet

Within the framework of the Canonical Formalism in the extended phase space,a general Hamiltonian is investigated that covers a wide class of radial intermediaries accounting for themajor secular effects due to a planet's oblateness perturbations.An analytical, closed-form solution for this generic Hamiltonian is developed in terms of elementary functions via the corresponding Hamilton-Jacobi equation. The analytical solution so obtained can be contemplated according to a simple geometrical and dynamical interpretation in Keplerian language by means of the usual relations characterizing elliptic elements along ahypothetic Keplerian motion.Appropriate choices for the terms appearing in the proposed Hamiltonian lead to recovering the analogues of some well-known, classical radial intermediaries (those introduced by Deprit and the one built by Alfriend and Coffey), but also certain new ones derived by Ferrándiz for the Main Problem in the Theory of Artificial Satellites of the Earth. In any case, the results are also applicable to problems dealing with orbital motion of other planetary satellites.The generality of this pattern leads to asystematic obtaining of solutions to the considered intermediaries: special choices of the Hamiltonian yield the correspondinganalytical solution to the respective intermediary problem.