Modeling and predicting the occupancy in a China hub airport terminal using Wi-Fi dataAirport terminalWi-fi dataDwell time distributionBayesian modelPredictive modelThe research on building energy consumption of airport terminal is of great importance, especially considering the rapid development of civil...
Soil analysis, Precision farming, Soil to Harvest, Crop modeling, AI, Precision Farming, Regenerative Farming, Multispectral Vision for Farming, Crop health, yield prediction, rice, sugarcane, sweet corn, cassava, potato, South East Asia, FarmAI, Farming
Census data is ubiquitous however, and many non-profits are well-versed in technologies like the Census’American FactFinderand The Reinvestment Fund’sPolicyMap. Thus, it seems reasonable to develop forecasts using these data before building comparable models using the more expensive, high resolution...
Aspects of the methods were validated using real data. Conclusions A deterministic method was developed to predict the accuracy of GEBV in selection candidates in a closed breeding population. The population parameter Me that is required for these predictions can be derived from an available ...
Football outsiders almanac 2013: the essential guide to the 2013 NFL and college football seasons. Seattle, WA: CreateSpace; 2013. Google Scholar [25] Schumaker RP, Solieman OK, Chen H. Predictive modeling for sports and gaming. In: Schumaker RP, Solieman OK, Chen H, Sports data mining....
Demographic estimation refers to predicting characteristics of existing customers and potential target customers using advanced statistical modeling. For example, gender, location, age, and other characteristics can be estimated, then used to predict the NPS scores with greater accuracy. ...
We have searched the literature, but we haven’t found any comparable machine learning modeling work. Our aim is to predict household size from electricity energy data, which can be part of Advanced Metering Infrastructure (AMI) or billing data. We innovated our deep learning architecture, after...
Compared to the prevailing research on operational risk modelling (see e.g. Cox2012; MacKenzie2014), cyber risk analyses are still very limited (Eling2020).Footnote1This lack of research is often linked to the limited availability of cyber loss data (Maillart and Sornette2010; Biener et al.201...
Using mortuary and burial data to place COVID-19 in Lusaka, Zambia within a global context Article Open access 29 June 2023 Introduction The first cases of COVID-19 in the United Kingdom were confirmed on 31 January 20201. Despite implementation of non-pharmaceutical interventions, including ...
Here, we train a deep learning classifier to provide an early warning signal for the five local discrete-time bifurcations of codimension-one. We test the classifier on simulation data from discrete-time models used in physiology, economics and ecology, as well as experimental data of ...