Application of Support Vector Machines in Assessing Conceptual Cost Estimates

Total conceptual cost estimates and the assessment of the quality of these estimates are critical in the early stages of a building construction project. In this study, the support vector machine (SVM) model for assessing the quality of conceptual cost estimates is proposed, and the application of SVM in construction areas is investigated. The results show that the SVM model assessed the quality of conceptual cost estimates slightly more accurately than the discriminant analysis model. This shows that using the SVM has potential in construction areas. In addition, the SVM model can assist clients in their evaluation of the quality of the estimated cost and the probability of exceeding the target cost, and in their decision on whether or not it is necessary to seek a more accurate estimate in the early stages of a project.     

Distributed memory systems for simulating artificial neural networks

In executing tasks involving intelligent information processing, the human brain performs better than the digital computer. The human brain derives its power from a large number [O(10¹¹)] of neurons which are interconnected by a dense interconnection network [O(10⁵) connections per neuron]. Artificial neural network (ANN) paradigms adopt the structure of the brain to try to emulate the intelligent information processing methods of the brain. ANN techniques are being employed to solve problems in areas such as pattern recognition, and robotic processing. Simulation of ANNs involves implementation of large number of neurons and a massive interconnection network. In this paper, we discuss various simulation models of ANNs and their implementation on distributed memory systems. Our investigations reveal that communication-efficient networks of distributed memory systems perform better than other topologies in implementing ANNs.     

Validation of a Method of Determination of Apparent Diffusivity Versus Composition in Solids

A method is presented for computing the values of apparent diffusivity in solids with respect to the concentration of the diffusing substance (water or sodium chloride). This method does not require any assumption upon the mathematical relationship between diffusivity and concentration. It can be applied to experimental measurements of local concentration versus position within the solid (profiles) with relatively few measurements (circa 10) and a mathematical smoothing of the experimental data by using an artificial neural network model. The method was first validated on simulated data obtained by using a constant diffusivity value and on experimental profiles when the relation between diffusivity and concentration was given. It was then applied to original experimental moisture profiles obtained by putting gelatin gels with different initial moisture contents into contact for up to 14 days. The method was also successfully applied to five sets of experimental moisture and sodium chloride profiles taken from the literature and obtained from different food products. Apparent diffusivities calculated by our method were found in agreement with those obtained by authors using different numerical methods to compute the diffusivity values.     

Determination of instantaneous corrosion rates and runoff rates of copper from naturally patinated copper during continuous rain events

Instantaneous corrosion rates of naturally patinated copper of varying age (16 months, 138 and 145 years) have been determined during continuous rain events in the laboratory with electrochemical impedance spectroscopy using a two-electrode cell. The two-electrode cell was found to yield the same information in bulk rainwater as a conventional three-electrode cell.Relatively constant corrosion rates, between 0.2 and 0.6 μm/y, were determined for samples having a two-layer structure with an inner brownish layer of cuprous oxide and an outer greenish layer of basic copper salts (138, 145 years). Samples with cuprous oxide as the dominating phase of the patina (16 months) showed higher and somewhat increasing corrosion rates during a rain event (from 0.6 to 1.2 μm/y). During a continuous rain event, corrosion rates were found to be approximately 10 (brownish patina) and 25 times (greenish patina) lower than corresponding instantaneous runoff rates. The first flush phenomena of the runoff process, with an increased concentration during first flush and a relatively constant concentration during steady state, was indirectly seen as an increase in solution conductivity during the first rain volume followed by relative constant value. The contribution of the concentration in the first flush to the total annual runoff rate was significant for panels having a greenish layer (138, 145 years) whereas it was negligible for panels having a brownish layer (16 months).     

Law,liability and expert systems

This paper examines some of the possible legal implications of the production, marketing and use of expert systems. The relevance of a legally useful definition of expert systems, comprising systems designed for use both by laymen and professionals, is related to the distinctions inherent in the legal doctrine underlying provision of goods and provision of services. The liability of the sellers and users of, and contributors to, expert systems are examined in terms of professional malpractice as well as product liability. A recurring theme indicates that legislators may be inclined to restrict possibilities of liability suits in order to avoid disincentives to the creation of expert systems.     

权力及正确权力观的标志

权力是统治阶级的权力,是统治阶级统治力量和意志的体现,是为统治阶级的利益服务的。在社会主义社会,权力是人民的权力。保证权力的人民性必须有相应的权力运行机制,在根本上则取决于领导干部树立正确的权利观,坚持为民执政、为民勤政、为民廉政。     

Forecasting of Turkey's net electricity energy consumption on sectoral bases

In this study forecast of Turkey's net electricity energy consumption on sectoral basis until 2020 is explored. Artificial neural networks (ANN) is preferred as forecasting tool. The reasons behind choosing ANN are the ability of ANN to forecast future values of more than one variable at the same time and to model the nonlinear relation in the data structure. Founded forecast results by ANN are compared with official forecasts.     

Semantic Web Mining: State of the art and future directions

Semantic Web Mining aims at combining the two fast-developing research areas Semantic Web and Web Mining. This survey analyzes the convergence of trends from both areas: More and more researchers are working on improving the results of Web Mining by exploiting semantic structures in the Web, and they make use of Web Mining techniques for building the Semantic Web. Last but not least, these techniques can be used for mining the Semantic Web itself.The Semantic Web is the second-generation WWW, enriched by machine-processable information which supports the user in his tasks. Given the enormous size even of today’s Web, it is impossible to manually enrich all of these resources. Therefore, automated schemes for learning the relevant information are increasingly being used. Web Mining aims at discovering insights about the meaning of Web resources and their usage. Given the primarily syntactical nature of the data being mined, the discovery of meaning is impossible based on these data only. Therefore, formalizations of the semantics of Web sites and navigation behavior are becoming more and more common. Furthermore, mining the Semantic Web itself is another upcoming application. We argue that the two areas Web Mining and Semantic Web need each other to fulfill their goals, but that the full potential of this convergence is not yet realized. This paper gives an overview of where the two areas meet today, and sketches ways of how a closer integration could be profitable.     

关于成都膨胀土地区边坡稳定性的探讨

成都市三环路建设中 ,膨胀土边坡稳定性研究是大家关心的重要课题。膨胀土边坡土体中的吸力变化直接影响到其稳定性 ,参照“人工神经网络技术”中的吸力经验公式 ,以三环路东一B标段的路堤边坡为例 ,采用“条分法”进行预测分析 ,并有针对性地进行防护处理取得了较好的效果。     

Integrating scheduling and control functions in computer integrated manufacturing using artificial intelligence

Proper integration of scheduling and control in Flexible Manufacturing Systems will make available the required level of decision-making capacity to provide a flexibly-automated, efficient, and quality manufacturing process. To achieve this level of integration, the developments in computer technology and sophisticated techniques of artificial intelligence (AI) should be applied to such FMS functions as scheduling. In this paper, we present an Intelligent Scheduling System for FMS under development that makes use of the integration of two AI technologies. These two AI technologies — Neural Networks and Expert Systems — provide the intelligence that the scheduling function requires in order to generate goodschedules within the restrictions imposed by real-time problems. Because the system has the ability to plan ahead and learn, it has a higher probability of success than conventional approaches. The adaptive behavior that will be achieved contribute to the integration of scheduling and control in FMS.