AIMC Topic: Commerce

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Predicting nationwide obesity from food sales using machine learning.

Health informatics journal May 19, 2019
The obesity epidemic progresses everywhere across the globe, and implementing frequent nationwide surveys to measure the percentage of obese population is costly. Conversely, country-level food sales information can be accessed inexpensively through ...
Humans Obesity Food Commerce Machine Learning Support Vector Machine
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A New Approach for Construction of Geodemographic Segmentation Model and Prediction Analysis.

Computational intelligence and neuroscience May 13, 2019
Customer retention is invariably the top priority of all consumer businesses, and certainly it is one of the most critical challenges as well. Identifying and gaining insights into the most probable cause of churn can save from five to ten times in t...
Commerce Humans Forecasting Consumer Behavior Machine Learning
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Forecasting stock prices with a feature fusion LSTM-CNN model using different representations of the same data.

PloS one Feb 15, 2019
Forecasting stock prices plays an important role in setting a trading strategy or determining the appropriate timing for buying or selling a stock. We propose a model, called the feature fusion long short-term memory-convolutional neural network (LST...
Neural Networks, Computer Models, Economic Commerce
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Artificial Intelligence Crime: An Interdisciplinary Analysis of Foreseeable Threats and Solutions.

Science and engineering ethics Feb 14, 2019
Artificial intelligence (AI) research and regulation seek to balance the benefits of innovation against any potential harms and disruption. However, one unintended consequence of the recent surge in AI research is the potential re-orientation of AI t...
Interdisciplinary Research Drug Trafficking Forecasting Humans Fraud Artificial Intelligence Social Media Sex Offenses Commerce Liability, Legal Crime
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Stock Market Forecasting Using Restricted Gene Expression Programming.

Computational intelligence and neuroscience Feb 5, 2019
Stock index prediction is considered as a difficult task in the past decade. In order to predict stock index accurately, this paper proposes a novel prediction method based on S-system model. Restricted gene expression programming (RGEP) is proposed ...
Neural Networks, Computer Algorithms Forecasting Humans Commerce Marketing Models, Genetic Models, Economic
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Improving Stock Closing Price Prediction Using Recurrent Neural Network and Technical Indicators.

Neural computation Aug 27, 2018
This study focuses on predicting stock closing prices by using recurrent neural networks (RNNs). A long short-term memory (LSTM) model, a type of RNN coupled with stock basic trading data and technical indicators, is introduced as a novel method to p...
Commerce Neural Networks, Computer Models, Economic
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Using machine learning to evaluate treatment effects in multiple-group interrupted time series analysis.

Journal of evaluation in clinical practice Jun 11, 2018
RATIONALE, AIMS, AND OBJECTIVES: Interrupted time series analysis (ITSA) is a popular evaluation methodology in which a single treatment unit's outcome is studied over time, and the intervention is expected to "interrupt" the level and/or trend of th...
Interrupted Time Series Analysis Smoking Prevention Discriminant Analysis California Program Evaluation Commerce Research Design Propensity Score Humans Treatment Outcome Machine Learning Evaluation Studies as Topic
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Market penetration of intersection AEB: Characterizing avoided and residual straight crossing path accidents.

Accident; analysis and prevention Mar 30, 2018
Car occupants account for one third of all junction fatalities in the European Union. Driver warning can reduce intersection accidents by up to 50 percent; adding Autonomous Emergency Braking (AEB) delivers a reduction of up to 70 percent. However, t...
Environment Protective Devices European Union Deceleration Motor Vehicles Commerce Humans Wounds and Injuries Accidents, Traffic Artificial Intelligence Germany Automobile Driving Vision, Ocular Technology Automation Emergencies
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Predictability of machine learning techniques to forecast the trends of market index prices: Hypothesis testing for the Korean stock markets.

PloS one Nov 14, 2017
The prediction of the trends of stocks and index prices is one of the important issues to market participants. Investors have set trading or fiscal strategies based on the trends, and considerable research in various academic fields has been studied ...
Models, Economic Republic of Korea Commerce Support Vector Machine Machine Learning Forecasting
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Artificial neural network and SARIMA based models for power load forecasting in Turkish electricity market.

PloS one Apr 20, 2017
Load information plays an important role in deregulated electricity markets, since it is the primary factor to make critical decisions on production planning, day-to-day operations, unit commitment and economic dispatch. Being able to predict the loa...
Electricity Forecasting Neural Networks, Computer Turkey Models, Statistical Commerce
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