Data Driven Modeling Techniques
Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology Part 1: Concepts and methodology
... Wu et al. (2007) applied a modular support vector machine (SVM) model, termed distributed SVR (D-SVR), with a two step Genetic Algorithm parameter optimization method, to carry out prediction of water level in a river. ...
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Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology Part 2: Application
... All techniques were found to perform on ...Nonlinear techniques, such as ANNs, will not perform ...by techniques that can outperform MLR, yet have the ability to adapt to linear ...of data ...
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A data-driven, piecewise linear approach to modeling human motions
... make modeling approaches that assume much weaker priors more attrac- ...reduction techniques such as principal component analysis, and they searched for a inverse kinematic solution in that ...in ...
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Data-Driven Modeling, Control and Tools for Cyber-Physical Energy Systems
... balance-based techniques for building thermal loads that allow for simultaneous calculation of radiant and con- vective effects at both interior and exterior surface during each time ...detailed modeling ...
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Data-driven techniques to estimate parameters in the homogenized energy model for shape memory alloys
... for modeling hysteresis in ferroelectric, ferromagnetic, and ferroelastic ...homogenization techniques, based on the assumption that quantities such as inter- action and coercive fields are manifestations ...
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Application of several data-driven techniques to predict a standardized precipitation index
... In this study, we used large-scale climate indi- ces for predicting the standard precipitation index (SPI). Among the several proposed drought moni- toring indices, SPI has widespread application for describing and ...
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Iterative Receiver Techniques for Data-Driven Channel Estimation and Interference Mitigation in Wireless Communications
... system modeling, two space-time transmission techniques, namely Alam- outi STC and SM are ...The modeling of Alamouti STC is based on the assumption that the channel is not varying for two-symbol ...
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Agricultural Data Modeling and Yield Forecasting using Data Mining Techniques
... using data mining techniques. Data mining techniques extract hidden knowledge through data analysis, unlike statistical ...agronomic data for the paddy ...
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Data-Driven Haptic Modeling and Rendering of Realistic Virtual Textured Surfaces
... texture modeling techniques have created haptic textures that depend on both user force and ...of data-driven decaying sinusoids at the material’s characteristic fre- quency ...
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Data-Driven Predictive Modeling of Neuronal Dynamics using Long Short-Term Memory
... dynamical modeling in ...and modeling in [16], [17], ...to modeling dynamical systems [20], [21], [22] mitigate the vanishing gradient problem but suffer from poor early trajectory predictive ...
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Data Driven Analytical Modeling of Power Transformers
... Abstract: In power systems there are complex transformer structures, whose accurate analysis is not possible using the techniques available today. This paper presents a systematic data driven ...
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A data-driven framework for neural field modeling
... Patient-specific data from electrophysiological recordings is readily available in the clinical setting, particu- larly from epilepsy surgery patients, suggesting an opportunity to make the patient-specific link ...
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Computational Intelligence based Data Driven Modeling: A case Study in Hydrology
... intelligence techniques such as Fuzzy Logic (FL) or Differential Evolution (DE) based modeling to accomplish the optimal behavior and higher accuracy of the ...
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Application of Hierarchical Linear Models/Linear Mixed effects Models in School Effectiveness Research
... cross-level data: In educational research, it is often the case that a researcher is interested in investigating the relationships between environmental factors ...cross-level data is to aggregate student ...
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—BASHYT, Web Information System,
... complex modeling environment for inland water – marine water management and the integration of such modeling system within a web based technological framework optimised for data management and ...
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Group Method of Data Handling for Modeling Magnetorheological Dampers
... for modeling MR200 damper in the context of sys- tem ...training. Modeling the MR200 damper is done in forward and inverse modes where force and vol- tages are being predicted ...GMDH-based modeling ...
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Modeling Spatio-temporal Malaria Risk Using Remote Sensing and Environmental Factors
... ground data for mapping the malaria risk and its monthly temporal ...patient data (malaria incidence per 1000 persons) obtained from the health department, danger zone (percent) map and population at risk ...
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A Review of Data Warehousing and Business Intelligence in different perspective
... of data, queries are processed in batch ...of data. When complex source data need to be accessed, managed query tools are to be ...source data on a fairly simple ...the data sources and ...
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Techniques to Improve the Usability of Software Signature Based Data Dependence Profilers for Feedback Driven Optimizations
... Accuracy prediction heuristic works across all the workloads and all different signature configurations. In incremental profiling, even though there is some redundancy involved, this technique shows the improved ...
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Analysis of plant-wide disturbances through data-driven techniques and process understanding
... Off-line diagnosis of a root cause was accomplished using a signature for non-linearity that grows stronger closer to the source (Thornhill et. al, 2001b). The non-linearity test determines whether a time series could ...
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