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An organization needs to comprehend their customers and clients conduct, inclinations, and future needs which rely on their past conduct. Web usage mining is an intuitive research point in which customers and clients' session grou...
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An organization needs to comprehend their customers and clients conduct, inclinations, and future needs which rely on their past conduct. Web usage mining is an intuitive research point in which customers and clients' session grouping is done to comprehend the exercises. This exploration examines the issue of mining and breaking down incessant example and particularly centered around lessening the quantity of standards utilizing shut example procedure and it likewise diminish filters the span of the database utilizing agglomerative grouping strategy. In the present work, a novel technique for design mining is introduced to tackle the issue through profile-based closed sequential pattern mining utilizing agglomerative clustering(PCSPAC). In this research, the proposed method is an improved version of Weblog mining techniques and to the online navigational pattern forecasting. In the proposed approach, first, we store the Web data which is accessed by the user and then find the pattern. Items with the same pattern are merged and then the closed frequent set of Web pages is found. Main advantage of our approach is that when the user next time demands for the same item then it will search only partial database, not in whole data. There is no need to take input as number of clusters. Experimental results illustrate that proposed approach reduces the search time with more accuracy.
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Digital data increase on servers with time which resulted in different researchers focusing on this field. Various issues are arising on the server such as data handling, security, maintenance, etc. In this paper, an approach for ...
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Digital data increase on servers with time which resulted in different researchers focusing on this field. Various issues are arising on the server such as data handling, security, maintenance, etc. In this paper, an approach for the document retrieval is proposed which efficiently fetches the document according to the query which is given by user. Here hash-based indexing of the dataset document was done by utilizing term features. In order to provide privacy for the terms, each of this is identified by a unique number and each document has its hash index key for identification. Experiment was done on real and artificial dataset. Results show that NDCG, precision, and recall parameter of the work are better as compared to previous work on different size of datasets.
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The global energy system is transforming with the consideration of a growing population with rising living standards that will need more energy. Simultaneously, the world must find ways to reduce greenhouse gas emissions and provi...
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The global energy system is transforming with the consideration of a growing population with rising living standards that will need more energy. Simultaneously, the world must find ways to reduce greenhouse gas emissions and provide sustainable energy production. As electricity is the fastest-growing part of the energy system and thus shifting to renewable energy production systems is the need of the hour. IEA reports that the Sun could be one of the largest resources for energy production for the upcoming ‘net zero goals’ of the world. Rapid decrease in the cost of installation and availability of solar radiation are major advantages for adoption, although this mode of generation of energy has a variable output which is influenced by several parameters. Hence solar energy forecasting is crucial to understand and predict the output of production, the demand of the consumers, and optimizing the dispatch of the electricity from grids to users. In this paper, we have analyzed innovative methodologies for forecasting solar energy radiation. Moreover, it provides a review and comparative analysis on various Artificial Neural Networks (ANN), Probabilistic and Statistical, and Time-Series based models used for estimating solar irradiation. Each of these models have been trained and tested in different geographical regions, weather conditions, and corresponding relevant parameters, which would provide an insight on efficient model selection and optimization for predicting short and long-term solar irradiation. Further, we have discussed some challenges while forecasting solar irradiation and future research direction in this domain.
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摘要 :
The global energy system is transforming with the consideration of a growing population with rising living standards that will need more energy. Simultaneously, the world must find ways to reduce greenhouse gas emissions and provi...
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The global energy system is transforming with the consideration of a growing population with rising living standards that will need more energy. Simultaneously, the world must find ways to reduce greenhouse gas emissions and provide sustainable energy production. As electricity is the fastest-growing part of the energy system and thus shifting to renewable energy production systems is the need of the hour. IEA reports that the Sun could be one of the largest resources for energy production for the upcoming ‘net zero goals’ of the world. Rapid decrease in the cost of installation and availability of solar radiation are major advantages for adoption, although this mode of generation of energy has a variable output which is influenced by several parameters. Hence solar energy forecasting is crucial to understand and predict the output of production, the demand of the consumers, and optimizing the dispatch of the electricity from grids to users. In this paper, we have analyzed innovative methodologies for forecasting solar energy radiation. Moreover, it provides a review and comparative analysis on various Artificial Neural Networks (ANN), Probabilistic and Statistical, and Time-Series based models used for estimating solar irradiation. Each of these models have been trained and tested in different geographical regions, weather conditions, and corresponding relevant parameters, which would provide an insight on efficient model selection and optimization for predicting short and long-term solar irradiation. Further, we have discussed some challenges while forecasting solar irradiation and future research direction in this domain.
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This study provides optimum time spent from a source to destination using fixed traffic-signal phase and timing (SPAT) information of each signal within a given route. Each section in the route requires different average speed for...
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This study provides optimum time spent from a source to destination using fixed traffic-signal phase and timing (SPAT) information of each signal within a given route. Each section in the route requires different average speed for travelling in diversified traffic conditions. Here genetic algorithm is used to find the optimum average speed in each section, so that overall travel time spent from source to destination is minimized. This study provides the information about the best possible time to start, within duration of 10 minutes from current time, so that the total time spent from the source to destination is minimized. When a journey starts at a particular time, it is possible to minimize the total travel time by estimating average speeds in different sections between source and destination.
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This study provides optimum time spent from a source to destination using fixed traffic-signal phase and timing (SPAT) information of each signal within a given route. Each section in the route requires different average speed for...
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This study provides optimum time spent from a source to destination using fixed traffic-signal phase and timing (SPAT) information of each signal within a given route. Each section in the route requires different average speed for travelling in diversified traffic conditions. Here genetic algorithm is used to find the optimum average speed in each section, so that overall travel time spent from source to destination is minimized. This study provides the information about the best possible time to start, within duration of 10 minutes from current time, so that the total time spent from the source to destination is minimized. When a journey starts at a particular time, it is possible to minimize the total travel time by estimating average speeds in different sections between source and destination.
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This paper describes the journey of adapting Agile-Scrum in a project, referred here as Global Configurator Project (GCP), where the project members are distributed across locations in Germany, India, and U. S. Here, we will be di...
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This paper describes the journey of adapting Agile-Scrum in a project, referred here as Global Configurator Project (GCP), where the project members are distributed across locations in Germany, India, and U. S. Here, we will be discussing about the practices like new taxonomy on scrum roles, scaling scrum with actually using Scrum of scrums and evolving cross-functional multi-skilled and self-managed feature team from silos components teams. This paper also measures the impact of our practices on communication and collaboration at the project level. This paper will be useful for scrum masters, product owners, and project managers while adapting Scrum.
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摘要 :
This paper describes the journey of adapting Agile-Scrum in a project, referred here as Global Configurator Project (GCP), where the project members are distributed across locations in Germany, India, and U.S. Here, we will be dis...
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This paper describes the journey of adapting Agile-Scrum in a project, referred here as Global Configurator Project (GCP), where the project members are distributed across locations in Germany, India, and U.S. Here, we will be discussing about the practices like new taxonomy on scrum roles, scaling scrum with actually using Scrum of scrums and evolving cross-functional multi-skilled and self-managed feature team from silos components teams. This paper also measures the impact of our practices on communication and collaboration at the project level. This paper will be useful for scrum masters, product owners, and project managers while adapting Scrum.
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摘要 :
This paper describes the journey of adapting Agile-Scrum in a project, referred here as Global Configurator Project (GCP), where the project members are distributed across locations in Germany, India, and U. S. Here, we will be di...
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This paper describes the journey of adapting Agile-Scrum in a project, referred here as Global Configurator Project (GCP), where the project members are distributed across locations in Germany, India, and U. S. Here, we will be discussing about the practices like new taxonomy on scrum roles, scaling scrum with actually using Scrum of scrums and evolving cross-functional multi-skilled and self-managed feature team from silos components teams. This paper also measures the impact of our practices on communication and collaboration at the project level. This paper will be useful for scrum masters, product owners, and project managers while adapting Scrum.
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With the rapid development of digital photos that can be taken at a very low cost using a low powered device, there is a demand for programmes that can edit images for users who have no technical expertise of image editing. We've ...
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With the rapid development of digital photos that can be taken at a very low cost using a low powered device, there is a demand for programmes that can edit images for users who have no technical expertise of image editing. We've employed multiple Machine Learning models of GAN -Generative Adversarial Network - and algorithms to extract information from photographs and produced two modules of it summed up as “AI Photo Editor” which can be used as an all-in-one image editor based on the same principle. Using the input satellite image as a starting point, one of the modules can remove various small things from the image, while another one can create the “Map View.” It can also be quite beneficial in terms of providing datasets/databases for other Machine Learning and Neural Network models.
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