Conceptual Prediction Model Research Articles

Assessment of Streamflow Variability with Upgraded HydroClimatic Conceptual Streamflow Model

HydroClimatic Conceptual Streamflow (HCCS) model is a conceptual model for prediction and future assessment of daily streamflow using climate inputs and time-varying watershed characteristics. However, without denying its useful salient features in a changing climate, applicability of the HCCS model is limited to the basins without any major man-made river structure(s), such as reservoirs. Considering this, the originally proposed HCCS model is upgraded (hereinafter ‘upgraded HCCS model’) to accommodate the human-intervened release from such structures within the basin, if any, and to include routing component through the river channels without using rigorous information from the river channels. The upgraded HCCS model is expected to be useful to assess (i) the effect on the streamflow at downstream due to upstream dam release, and (ii) the long-term modification required in the reservoir/dam operation under a changing climate for ensuring water-availability in downstream. The upgraded HCCS model is applied to three river basins for assessing the future streamflow characteristics. Two of these basins have one each and the third basin has two major man-made river structures within them. Hadley Centre Coupled Model, version 3 (HadCM3) simulated climate variables till 2035 are used as inputs for demonstration. The model predicts an increase in streamflow in future. In general, the upgraded HCCS model can be applied to any tropical river basin having major man-made river structure(s) for daily streamflow prediction as well as assessment of future streamflow variation considering the changing climate and watershed characteristics.

Design and implementation of a standardized framework to generate and evaluate patient-level prediction models using observational healthcare data.

ObjectiveTo develop a conceptual prediction model framework containing standardized steps and describe the corresponding open-source software developed to consistently implement the framework across computational environments and observational healthcare databases to enable model sharing and reproducibility.MethodsBased on existing best practices we propose a 5 step standardized framework for: (1) transparently defining the problem; (2) selecting suitable datasets; (3) constructing variables from the observational data; (4) learning the predictive model; and (5) validating the model performance. We implemented this framework as open-source software utilizing the Observational Medical Outcomes Partnership Common Data Model to enable convenient sharing of models and reproduction of model evaluation across multiple observational datasets. The software implementation contains default covariates and classifiers but the framework enables customization and extension.ResultsAs a proof-of-concept, demonstrating the transparency and ease of model dissemination using the software, we developed prediction models for 21 different outcomes within a target population of people suffering from depression across 4 observational databases. All 84 models are available in an accessible online repository to be implemented by anyone with access to an observational database in the Common Data Model format.ConclusionsThe proof-of-concept study illustrates the framework’s ability to develop reproducible models that can be readily shared and offers the potential to perform extensive external validation of models, and improve their likelihood of clinical uptake. In future work the framework will be applied to perform an “all-by-all” prediction analysis to assess the observational data prediction domain across numerous target populations, outcomes and time, and risk settings.

Recommendation on semantic web pages based on conceptual prediction model

The development of trhe web has made a major test for guiding the client to the pages in their regions.Useful knowledge disclosure from web use information and acceptable learning portrayal for successful page suggestion are urgent and testing.In this paper we propose a novel technique to effectively give a better site page proposal through semantic upgrade by coordinating the space and web use learning of a site.Two new models are proposed to the learning.Semantic system is used to the web pages and the relations between the pages.Conceptional model produces a semantic system for web use information,which is the combination of learning and web use information.Various inquires have been created to inquiry about these learning base.Based on these questions ,an arrangement of suggestion methodologies have been proposed to produce fitting site page proposals to the client.The suggestion comes about have been contrasted and the outcomes got from a progressed existing Web Usage Mining(WUM)strategy.The exploratory outcomes show that the proposed technique delivers essentialy higher execution than the WUM technique.

A conceptual prediction model for seasonal drought processes using atmospheric and oceanic standardized anomalies: application to regional drought processes in China

Abstract. Reliable drought prediction is fundamental for water resource managers to develop and implement drought mitigation measures. Considering that drought development is closely related to the spatial–temporal evolution of large-scale circulation patterns, we developed a conceptual prediction model of seasonal drought processes based on atmospheric and oceanic standardized anomalies (SAs). Empirical orthogonal function (EOF) analysis is first applied to drought-related SAs at 200 and 500 hPa geopotential height (HGT) and sea surface temperature (SST). Subsequently, SA-based predictors are built based on the spatial pattern of the first EOF modes. This drought prediction model is essentially the synchronous statistical relationship between 90-day-accumulated atmospheric–oceanic SA-based predictors and SPI3 (3-month standardized precipitation index), calibrated using a simple stepwise regression method. Predictor computation is based on forecast atmospheric–oceanic products retrieved from the NCEP Climate Forecast System Version 2 (CFSv2), indicating the lead time of the model depends on that of CFSv2. The model can make seamless drought predictions for operational use after a year-to-year calibration. Model application to four recent severe regional drought processes in China indicates its good performance in predicting seasonal drought development, despite its weakness in predicting drought severity. Overall, the model can be a worthy reference for seasonal water resource management in China.

Reconstruction of conceptual prediction model for the Three Rainfall Patterns in the summer of eastern China under global warming

With the influence of global warming, the global climate has undergone significant inter-decadal variation since the late 1970s. Although El Nino-Southern Oscillation (ENSO) has been the strongest signal for predicting global climate inter-annual variability, its relation with the summer rainfall in China has significantly changed, and its indicative function on the summer rainfall in China has weakened. This has led to a significant decrease in the accuracy rate of early conceptual prediction models for the Three Rainfall Patterns in the summer of eastern China. On the basis of the difference analysis of atmospheric circulation system configuration in summer, as well as the interaction of ocean and atmospheric in previous winter between two phases, i.e. before and after the significant global warming (1951 to 1978 and 1979 to 2012, respectively), we concluded that (1) Under different inter-decadal backgrounds, the atmospheric circulations that impacted the Three Rainfall Patterns in the summer of eastern China showed consistency, but in the latter phase of the global warming, the Western Pacific Subtropical High (WPSH) was on the strong side, the position of which was in the south, and the blocking high in the Eurasia mid-high latitudes was active, while the polar vortex extended to the south, and meridional circulation intensified. This circulation background may have been conducive to the increase of the circulation frequency of Patterns II and III, and the decrease of the circulation frequency of Pattern I, thus leading to more Patterns II and III and fewer Pattern I in the summer rainfall of eastern China. (2) In the former phase, the corresponding previous winter SST fields of different rainfall patterns showed visible differences. The impact of ENSO on North Pacific Oscillation (NPO) was great, and the identification ability of which on Patterns I and II of summer rainfall was effective. In the latter phase, this identification ability decreased, while the impact of ENSO on the Pacific/North American (PNA) teleconnection pattern increased, and the identification ability of the PNA on Patterns II and III also increased. Based on the new inter-decadal climate background, this study reconstructs the conceptual prediction model for the Three Rainfall Patterns in summer of eastern China by using the previous winter PNA and the Eurasian (EU) teleconnection indexes. The fitting effect was satisfying, though it is necessary to be further tested.

Web-Page Recommendation Based on Web Usage and Domain Knowledge

Web-page recommendation plays an important role in intelligent Web systems. Useful knowledge discovery from Web usage data and satisfactory knowledge representation for effective Web-page recommendations are crucial and challenging. This paper proposes a novel method to efficiently provide better Web-page recommendation through semantic-enhancement by integrating the domain and Web usage knowledge of a website. Two new models are proposed to represent the domain knowledge. The first model uses an ontology to represent the domain knowledge. The second model uses one automatically generated semantic network to represent domain terms, Web-pages, and the relations between them. Another new model, the conceptual prediction model, is proposed to automatically generate a semantic network of the semantic Web usage knowledge, which is the integration of domain knowledge and Web usage knowledge. A number of effective queries have been developed to query about these knowledge bases. Based on these queries, a set of recommendation strategies have been proposed to generate Web-page candidates. The recommendation results have been compared with the results obtained from an advanced existing Web Usage Mining (WUM) method. The experimental results demonstrate that the proposed method produces significantly higher performance than the WUM method.

Conceptual Model for Prediction of FRP-Concrete Bond Strength under Moisture Cycles

Fiber-reinforced polymer (FRP) retrofit systems for concrete structural members such as beams, columns, slabs, and bridge decks have become increasingly popular as a result of extensive studies on short-term debonding behavior. Nevertheless, long-term performance and durability issues regarding debonding behavior in such strengthening systems still remain largely uncertain and unanswered. Because of its composite nature, the effectiveness of the strengthening system depends on the properties of the interfaces between the three constituent materials; namely, concrete, epoxy, and FRP. Certain factors, including those related to environmental exposures, can cause degradation of the interface properties during service life. This is particularly critical when predicting service life and planning maintenance of FRP-strengthened concrete structures. In this study, effect of moisture on an FRP-concrete bond system is characterized by means of the tri-layer fracture toughness, which can be obtained experimentally from peel and shear fracture tests. Fracture specimens were conditioned under various durations and numbers of wet-dry cycles at room temperature and 50°C. An irreversible weakening in bond strength was observed in fracture specimens under moisture cyclic condition. A conceptual model is developed based on the experimental results of the fracture specimens under variable cyclic moisture conditions for the bond strength prediction of the FRP-concrete bond system. A numerical study of a precracked FRP-strengthened reinforced concrete beam is then performed to show potential application of the proposed predictive model.

Modified conceptual model for predicting the tendency of alluvial channel adjustment induced by human activities

After a discussion about some limitations of Schumm’s conceptual model for prediction of river metamorphosis, this study introduces the channel boundary material as an independent variable, and thereby establishes a conceptual model that can be used to predict the direction of channel adjustment induced by human activities. This model has been tested by data from natural rivers and a laboratory model river, and can be used to explain the complex behavior of channel adjustment after reservoir construction.