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The widely used geospatial web services technology has provided a new means for geospatial data interoperability. Web Map Service (WMS) is a standardized geospatial web service from the Open Geospatial Consortium (OGC). WMSs can be used for requesting and producing maps on the Internet, and have been widely adopted in the Geographic Information System (GIS) community. These WMSs make remote sensing...
Hydrology time series prediction is significant. It is not only helpful to set the planning in daily configuration works of water resources, but also provides guidance for leaders to make decision, especially in some special case such as flood and seriously lack water. In order to solve the imbalance complexity of prediction model and complexity of samples and raise forecasting accuracy, combined...
Uncertainty prediction for ocean and climate predictions is essential for multiple applications today. Many-Task Computing can play a significant role in making such predictions feasible. In this manuscript, we focus on ocean uncertainty prediction using the Error Subspace Statistical Estimation (ESSE) approach. In ESSE, uncertainties are represented by an error subspace of variable size. To predict...
This paper presents a short-term prediction of fog occurrence based on suitable data mining methods. The whole process was implemented through CRISP-DM methodology that represents most commonly used approach for data mining. This methodology consists of six main phases, which we describe in this paper for our application: business understanding, data understanding, data preparation, modeling, evaluation...
Environmental risk management research is an established part of the Earth sciences domain, already known for using powerful computational resources to model physical phenomena in the atmosphere, oceans, and rivers. In this paper we explore how these data-intensive processes can be managed by machine-learning and data mining techniques to benefit the experts who produce daily weather predictions,...
Soft computing forecasting tools play an important role to forecast many complicated systems. In this paper, an effort has been made to use soft computing approaches to predict Dhaka daily temperatures for the period of 28 February 1945 to 27 August 2006. We have selected the fuzzy neuro model, the neuro genetic algorithm model as soft computing techniques. To compare results, a popular time series...
The true three-dimensional modeling is a common issue for geology, three-dimensional GIS, scientific is visualization and engineering application. This paper presented a new 3D data model that based on TEN, and introduced the TEN's generation algorithm and steps. The example indicated this algorithm can produce the tetrahedron unit mesh of the arbitrary shape three-dimensional geological body well.
There is coexistence of different metadata standards in the field of Earth Science. It causes many challenging difficulties of data Sharing and Management in Earth Science. In order to deal with the problem, a multi-standard compatible metadata framework named "XMCMF" is proposed by extending the tree model and introducing object types, inheritance mechanisms and alias mechanisms. XMCMF...
This paper proposes a new hurricane intensity prediction model, WFL-EMM, which is based on the data mining techniques of feature weight learning (WFL) and Extensible Markov Model (EMM). The data features used are those employed by one of the most popular intensity prediction models, SHIPS. In our algorithm, the weights of the features are learned by a genetic algorithm (GA) using historical hurricane...
Extensive computing power has been used to tackle issues such as climate changes, fusion energy, and other pressing scientific challenges. These computations produce a tremendous amount of data, however, many of the data analysis programs currently only run a single processor. In this work, we explore the possibility of using the emerging cloud computing platform to parallelize such sequential data...
The spatial data sharing mechanisms is important in the technical infrastructure of cloud computing or GRID computing, Many researchers have focused on the centralized resource pool and global-local two-layer model but little work considers the availability and practicability of universal discovery description and integration and mechanisms of supporting long transaction management. In this paper,...
Critical climate applications like cyclone tracking and earthquake modeling require high-performance simulations and online visualization simultaneously performed with the simulations for timely analysis. Remote visualization of critical climate events enables joint analysis by geographically distributed climate science community. However, resource constraints including limited storage and slow networks...
This article describes the enablement of the MM5 Meteorological model as a Computational Grid Workflow. Considering the challenges involved in converting legacy high performance scientific applications as service based workflows, this article provides an in-depth analysis and solutions thereof to design a Grid service based workflow of HPC scientific applications. It also captures the need and design...
The Deep Water Horizon well blowout on April 20th 2010 discharged between 40,000-1.2 million tons of crude oil into the Gulf of Mexico. In order to understand the fate and impact of the discharged oil, particularly on the environmentally sensitive Florida Keys region, we have implemented a multi-component application which consists of many individual tasks that utilize a distributed set of computational...
Trajectory is defined as a movement of an object in space and time, which consists of a set of spatial and temporal data. Exploration of this dataset can be used to extract the movement behaviour of moving objects that is previously unknown. This research proposes several alternatives on how to retrieve information from trajectory dataset in a database system with the Antarctic's iceberg movements...
Currently, numerically simulated synthetic seismograms are widely used by seismologists for seismological inferences. The generation of these synthetic seismograms requires large amount of computing resources, and the maintenance of these observed seismograms requires massive storage. Traditional high-performance computing platforms is inefficient to handle these applications because rapid computations...
By analyzing the relation between mud logging data, well logging data and formation drillability, a novel method for predicting formation drillability based on particle swarm optimization and support vector machine (PSO-SVM) is proposed. The prediction model for formation drillability is established using the data of drilling pressure, rotary speed, hydraulic horsepower, bottom hole differential pressure,...
Ice charts have been widely used as a dominated approach or de facto data standard for organizing sea-ice data. These charts are sufficient for safer navigation, oil drilling and so on, but may not be suitable for advanced spatiotemporal analysis in climate studies such as change tracking, factor analysis and data simulation. In addition, sea-ice data presented in ice charts is difficult to integrate...
This paper uses back propagation (BP) neural network to modify manual observing system data to automatic observing system data in wind speed data. First, we prepare six factors which are wind speed data six hours ahead to one hour ahead as input data. The tests indict when these factors selected, the modify results are better than others. The training data used for the neural network is the data from...
Radar remote sensing technology has become an important method for stable and long-time rice monitoring for its capability to operate in all weather conditions. In this paper, the obtained main achievements on rice monitoring using ENVISAT ASAR data were reviewed and major results were summarized. The results showed that the multi-temporal and multi-polarization radar data has advantages in rice monitoring,...
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