A soitable data model and data structure make underground survey objects maintained and operated easier. This paper gives a formal definition for underground survey objects. By making use of the quotient topological s...A soitable data model and data structure make underground survey objects maintained and operated easier. This paper gives a formal definition for underground survey objects. By making use of the quotient topological space, the author studies the logical relations among underground survey objects, a partiallyordered space uuder some conditions. An example is given to show the data model’s possible applications.展开更多
Three dimensional object extraction and recognition (OER) from geographic data has been definitely one of more important topic in photogrammetry for quite a long time. Today, the capability of rapid generating high-de...Three dimensional object extraction and recognition (OER) from geographic data has been definitely one of more important topic in photogrammetry for quite a long time. Today, the capability of rapid generating high-density DSM increases the supply of geographic information but the discrete nature of the measuring makes more difficult to recognize correctly and to extract 3D objects from these surface. The proposed methodology wants to semi-automate some geographic objects clustering operations, in order to perform the recognition process. The clustering is a subjective process;the same set of data items often needs to be partitioned differently based on the application. Fuzzy logic gives the possibility to use in a mathematical process the uncertain information typical of human reasoning. The concept at the base of our proposal is to use the information contained in Image Matching or LiDAR DSM, and typically understood by the human operator, in a fuzzy recognition process able to combine the different input in order to perform the classification. So the object recognition approach proposed in our workflow integrates 3D structural descriptive components of objects, extracted from DSM, into a fuzzy reasoning process in order to exploit more fully all available information, which can contribute to the extraction and recognition process and, to handling the object’s vagueness. The recognition algorithm has been tested with to different data set and different objectives. An important issue is to apply the typical human process which allows to recognize objects in a range image in a fuzzy reasoning process. The investigations presented here have given a first demonstration of the capability of this approach.展开更多
In this paper, a multi objective, multireservoir operation model is proposed using Genetic algorithm (GA) under fuzzy environment. A monthly Multi Objective Genetic Algorithm Fuzzy Optimization (MOGAFU-OPT) model for ...In this paper, a multi objective, multireservoir operation model is proposed using Genetic algorithm (GA) under fuzzy environment. A monthly Multi Objective Genetic Algorithm Fuzzy Optimization (MOGAFU-OPT) model for the present study is developed in ‘C’ Language. The GA parameters i.e. population size, number of generations, crossover probability, and mutation probability are decided based on optimized val-ues of fitness function. The GA operators adopted are stochastic remainder selection, one point crossover and binary mutation. Initially the model is run for maximization of irrigation releases. Then the model is run for maximization of hydropower production. These objectives are fuzzified by assuming a linear membership function. These fuzzified objectives are simultaneously maximized by defining level of satisfaction (?) and then maximizing it. This approach is applied to a multireservoir system in Godavari river sub basin in Ma-harashtra State, India. Problem is formulated with 4 reservoirs and a barrage. The optimal operation policy for maximization of irrigation releases, maximization of hydropower production and maximization of level of satisfaction is presented for existing demand in command area. This optimal operation policy so deter-mined is compared with the actual average operation policy for Jayakwadi Stage-I reservoir.展开更多
文摘A soitable data model and data structure make underground survey objects maintained and operated easier. This paper gives a formal definition for underground survey objects. By making use of the quotient topological space, the author studies the logical relations among underground survey objects, a partiallyordered space uuder some conditions. An example is given to show the data model’s possible applications.
文摘Three dimensional object extraction and recognition (OER) from geographic data has been definitely one of more important topic in photogrammetry for quite a long time. Today, the capability of rapid generating high-density DSM increases the supply of geographic information but the discrete nature of the measuring makes more difficult to recognize correctly and to extract 3D objects from these surface. The proposed methodology wants to semi-automate some geographic objects clustering operations, in order to perform the recognition process. The clustering is a subjective process;the same set of data items often needs to be partitioned differently based on the application. Fuzzy logic gives the possibility to use in a mathematical process the uncertain information typical of human reasoning. The concept at the base of our proposal is to use the information contained in Image Matching or LiDAR DSM, and typically understood by the human operator, in a fuzzy recognition process able to combine the different input in order to perform the classification. So the object recognition approach proposed in our workflow integrates 3D structural descriptive components of objects, extracted from DSM, into a fuzzy reasoning process in order to exploit more fully all available information, which can contribute to the extraction and recognition process and, to handling the object’s vagueness. The recognition algorithm has been tested with to different data set and different objectives. An important issue is to apply the typical human process which allows to recognize objects in a range image in a fuzzy reasoning process. The investigations presented here have given a first demonstration of the capability of this approach.
文摘In this paper, a multi objective, multireservoir operation model is proposed using Genetic algorithm (GA) under fuzzy environment. A monthly Multi Objective Genetic Algorithm Fuzzy Optimization (MOGAFU-OPT) model for the present study is developed in ‘C’ Language. The GA parameters i.e. population size, number of generations, crossover probability, and mutation probability are decided based on optimized val-ues of fitness function. The GA operators adopted are stochastic remainder selection, one point crossover and binary mutation. Initially the model is run for maximization of irrigation releases. Then the model is run for maximization of hydropower production. These objectives are fuzzified by assuming a linear membership function. These fuzzified objectives are simultaneously maximized by defining level of satisfaction (?) and then maximizing it. This approach is applied to a multireservoir system in Godavari river sub basin in Ma-harashtra State, India. Problem is formulated with 4 reservoirs and a barrage. The optimal operation policy for maximization of irrigation releases, maximization of hydropower production and maximization of level of satisfaction is presented for existing demand in command area. This optimal operation policy so deter-mined is compared with the actual average operation policy for Jayakwadi Stage-I reservoir.
