Predictive modelling of multiperiod geoarchaeological resources at a river confluence: a case study from the Trent–Soar, UK

2006 ◽  
Vol 13 (4) ◽  
pp. 241-250 ◽  
Author(s):  
Chris J. Carey ◽  
Tony G. Brown ◽  
Keith C. Challis ◽  
Andy J. Howard ◽  
Lynden Cooper
Keyword(s):  
Predictive Modelling ◽  
River Confluence

Sugar factory audits, debottlenecking and efficiency improvement

2020 ◽  
pp. 607-612
Author(s):  
Bernard Coûteaux
Keyword(s):  
Evaluation Method ◽  
Predictive Modelling ◽  
Cane Sugar ◽  
Sugar Factory ◽  
Low Energy Consumption ◽  
Process Simulations ◽  
Capital Efficiency ◽  
Potential Improvement ◽  
Primary Focus

This paper elaborates on the key solutions offered by De Smet Engineers & Contractors (DSEC) to optimize the efficiency of cane sugar producing and processing facilities. In order to meet customer needs, DSEC offers proprietary predictive models built using the latest versions of specialized software. These models allow factory managers to envision the whole picture of increased operational and capital efficiency before it becomes reality. An integrated energy model and the CAPEX/OPEX evaluation method are discussed as ways to estimate and optimize costs, both for new greenfield projects and revamping of existing factories. The models demonstrate that factory capacities can be successfully increased using equipment that is already available. Special attention is paid to crystallization and centrifugation process simulations and the potential improvement of the global energy balance. One case study shows the transformation of a beet sugar factory into a refinery to process raw cane sugar after beet crop season and the second case shows the integration of a refinery into a cane sugar factory. The primary focus of the article is optimization of the technological process through predictive modelling. DSEC’s suggested solutions, which lead to great improvements in a plant’s efficiency and its ability to obtain very low energy consumption, are discussed.

scholarly journals The Effects of Hydraulic Jumps Instability on a Natural River Confluence: The Case Study of the Chiaravagna River (Italy)

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 2027 ◽  
Author(s):  
Annalisa De Leo ◽  
Alessia Ruffini ◽  
Matteo Postacchini ◽  
Marco Colombini ◽  
Alessandro Stocchino
Keyword(s):  
Physical Model ◽  
Hydraulic Jump ◽  
Low Frequency ◽  
Water Levels ◽  
Entire Area ◽  
Hydraulic Conditions ◽  
River Confluence ◽  
Series Of Experiments ◽  
Small River Basin

The occurrence and the effects of hydraulic jump instabilities on a natural river confluence in a small river basin in Liguria (Italy) is here investigated. Hydraulic jump instability has been extensively studied in controlled and simplified laboratory rectangular flumes. In the present study, a scaled physical model of the Chiaravagna River and Ruscarolo Creek confluence has been used, retaining the realistic geometry of the reaches. This reach has been subject to frequent floods in the last twenty years and the entire area of the confluence has been redesigned to decrease the flood risk. A series of experiments has been performed varying the discharge on the two reaches and the geometrical configurations. Free surface levels and two dimensional horizontal velocities have been measured in several positions along the physical model. The analysis of the water levels and velocities reveals that oscillations characterised by large amplitude and low frequency occur under particular hydraulic conditions. These oscillations have been found to be triggered by the hydraulic jump toe instability of the smallest reach of the confluence. Aiming at reducing the amplitude of the oscillations, which can be of the order of the flow depth, possible constructive solutions have been tested to control or damp the oscillations. Indeed, the insertion of a longitudinal dyke at the confluence has proven to be an effective solution to limit the amplitude of the transversal oscillations.

scholarly journals The impact of significant input of fine sediment on benthic fauna at tributary junctions: a case study of the Bermejo-Paraguay River confluence, Argentina

Ecohydrology ◽  
2014 ◽  
Vol 8 (2) ◽  
pp. 340-352 ◽  
Author(s):  
Martín C. M. Blettler ◽  
Mario L. Amsler ◽  
Inés Ezcurra de Drago ◽  
Luis A. Espinola ◽  
Eliana Eberle ◽  
...  
Keyword(s):  
Benthic Fauna ◽  
Fine Sediment ◽  
Paraguay River ◽  
River Confluence ◽  
The Impact

scholarly journals Social Media Big Data Analytics for Demand Forecasting

2020 ◽  
Vol 28 (1) ◽  
pp. 103-120 ◽  
Author(s):  
Rehan Iftikhar ◽  
Mohammad Saud Khan
Keyword(s):  
Social Media ◽  
Big Data ◽  
Supply Chain ◽  
Demand Forecasting ◽  
Big Data Analytics ◽  
Predictive Modelling ◽  
Product Demand ◽  
Emotion Model ◽  
Improving Accuracy

Social media big data offers insights that can be used to make predictions of products' future demand and add value to the supply chain performance. The paper presents a framework for improvement of demand forecasting in a supply chain using social media data from Twitter and Facebook. The proposed framework uses sentiment, trend, and word analysis results from social media big data in an extended Bass emotion model along with predictive modelling on historical sales data to predict product demand. The forecasting framework is validated through a case study in a retail supply chain. It is concluded that the proposed framework for forecasting has a positive effect on improving accuracy of demand forecasting in a supply chain.

scholarly journals Predictive modelling of seabed habitats: case study of subtidal kelp forests on the coast of Brittany, France

2010 ◽  
Vol 157 (7) ◽  
pp. 1525-1541 ◽  
Author(s):  
Vona Méléder ◽  
Jacques Populus ◽  
Brigitte Guillaumont ◽  
Thierry Perrot ◽  
Pascal Mouquet
Keyword(s):  
Predictive Modelling ◽  
Kelp Forests

scholarly journals Simplifying Research Oriented to Practitioners and Policymakers: A Case Study of Predictive Modelling with Naive Bayes

2021 ◽  
Author(s):  
Troy Smith
Keyword(s):  
Model Comparison ◽  
Performance Metrics ◽  
Naive Bayes ◽  
Model Performance ◽  
Predictive Modelling ◽  
Target Population ◽  
Naïve Bayes ◽  
Offender Profiling ◽  
High Crime

The study examines the applicability of Naïve Bayes in predictive classification modelling using a case study of cybercrime victimization data. The goal of which was a targeted presentation of the benefits of Bayesian analysis in crime research geared to policymakers. The method is assessed using a Model-Comparison Approach and model performance metrics. The study shows that Naïve Bayes can be useful in predictive classification where the target population is small or difficult to acquire such as offender profiling and analysis of high crime areas. This is important as it provides a plausible option to traditional Frequentist methods, that overcome statistical limitations and provides results in a form easily conveyable to policymakers. Further, the conditional probability data produced makes future prediction transparent and can foster confidence in predicted outcomes. In particular, Directed Acyclic Graph can be easily used to represent the Naïve Bayes output allowing visualization of the relationships between variables.

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