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This paper describes expert systems for the aquatic ecosystem diagnostics including its dynamics in the changing climate and detection of stressful situations when anthropogenic processes are realized in the sea basin. Expert system is based on the monitoring data processing and simulation results that are delivered by series models describing basic ecological, hydrological, hydrochemical and geophysical...
Artificial Intelligence (AI) is a fast developing area that is applied to many daily problems, replacing the tried and true heuristics used by society for a long time. This paper provides a framework to estimate the value added by different steps and components used to create and apply AI models. Such estimations are useful to decide if deploying AI models makes economical sense, reported to the specific...
Substantial studies integrating experts' knowledge with statistical forecasting models have been implemented to investigate a long-lasting and disputing issue, the extent to which expert knowledge can improve forecasting performance. However, many current studies are not capable of applying experts' interval knowledge in forecasting. Experts are expected to be more competent and confident, given that...
The scarcity of potable water increasing day by day. Rivers are the main source of land water for industry and agricultural activity. Unexpected transforms in river low reasoned by imminent tremendous events may enforce grave dilapidation on river water quality and significant impacts on ecosystems. The aim of these lessons is to determine the quality category of water in river and to help extract...
Inference and domain knowledge are the foundation of a Knowledge-based System (KBS). Inference knowledge describes the steps or rules used to perform a task inference; making reference to the domain knowledge that is used. The inference knowledge is typically acquired from the domain experts and communicated to the system developers to be implemented in a KBS. The explicit representation of inference...
Most biomaterials are undergoing a process degradation faster than other materials. The biomaterials are often combined with other materials by various methods of treatment in order to ensure certain performance and functionality. Maintenance biomaterials must take into account both their particular as well as the evolution of experience accumulated. Treatment of the biomaterial, in many cases does...
This paper describes fuzzy logic expert system (FES) uses data about the Zero Moment Point (ZMP) position for automatically determining the gait phases. Simplified human body model is introduced for computation of ZMP position which is the input to the FES. Information about the type of gait phase is the output of FES. The designed fuzzy-rules based system was tested to evaluate the gait of twenty-two...
This paper presents the methodology and results of a recent research project SCETIST (2010–2013) devoted to foresight of selected artificial intelligence technologies. The AI trends and scenarios have been elicited using expert Delphi as well as via a simulation of a hybrid discrete-time and discrete-event control system. The system components include a complex information society model, which describes...
The poplar is shelterbelt species, because the poplar has the characters that are fast growth, adaptability, easy breeding, make protective and economic benefits etc, which has been widely used in the production and building. In order to improve the growth quality and the level of growth management of poplar, the paper applied modern information technologies such as neural network, expert system and...
Considering the growth and management of fruit tree, intelligent decision management technology based on modern information technology improves the quality of fruit tree production and meets the needs of modern agriculture, agricultural information technology includes neural networks, ontology, expert system, decision support system etc, and growth model has the function which can predict and manage,...
By analyzing the manual establishment process of the coal mine extraction-tunneling plans, the experiences and knowledge are obtained, and the knowledge sets of the coal mine extraction-tunneling plans are formed, then the technical and economic models are built. Combining the decision support system with the expert system, the advantages of quantitative calculation of the decision support system...
This research presents the Ok - build expert system for automatic detection of norm compliance in the construction domain. In the first step, the plan of the building, exported by the CAD tools using the Industry Foundation Classes (IFC) standard, is converted as Jess facts. Then, the construction is checked against the active regulatory norms represented as Jess rules.
Model-based diagnosis has a great advantage compared to other diagnostic methods. However, there are some problems existed in model-based method like large complexity, inefficient. This paper studies a state searching method using system conflicts to exclude large invalid state space and speed up the search procedure. All the tested candidate states are generated in best first order and expanded to...
This paper presents a methodology and software for hazard rate analysis of induction type watt-hour meters, considering the main variables related with the degradation process of these meters, for the Elektro Electricity and Services SA. The modeling developed to calculate the watt-hour meters hazard rate was implemented in a tool through a user friendly platform, in Delphi language, enabling not...
The Agro-ecological Decision Support System, MicroLEIS DSS, was applied to investigate and predict soil degradation in the province of El-Fayoum, one of the western desert areas of the Arab Republic of Egypt, with an area of 149,300 ha approximately. The Pantanal land evaluation model as one constituents of this DSS, was used for evaluating contamination risks of phosphorus, nitrogen, heavy metals...
Short term load forecasting for day ahead operations is an important task of an electric distribution company. Forecasting errors directly impact the economics of the distribution company in a market scenario. Many categories of methods like, expert system, artificial neural network and time series analysis, have been developed for short term load forecasting. We compare and contrast these methods...
Bayesian network is a powerful tool for scenario analysis and prediction. At present, future scenario is structured by combining the results of forecasting every variable. The dependency relationship between variables is neglected so that the result of scenario prediction often is unreliable. In this paper, a Bayesian network is built by combining subjective expert knowledge and objective data and...
Mechanism type selection is a critical problem often encountered in conceptual design stage of mechanical system. A BP neural network based approach to mechanism type selection is proposed, which capitalizes on the features of nonlinearity, self-organization, and fault tolerance of a neural network to implement classification and selection. By using appropriate data sets to train the neural network...
We presented a network comparison algorithm for predicting the conservative interaction regions in the cross-species protein-protein interaction networks (PINs). In the first place, We made use of the correlated matrix to represent the PINs. Then we standardized the matrix and changed it into a unique representation to facilitate to judge whether the subgraphs is isomorphic. Then we proposed a network...
Nowadays, the international community demands to develop new ways to diminish the effects on the growing environmental damage, either by changing development processes and products, or by developing new ways to make those existing products less harmful to the environment. This paper tries to develop an expert system based on fuzzy logic to reduce the pollution produced by spark ignition engines, taking...
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