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Forecasting stock prices with long-short term memory neural network based on attention mechanism.

PloS one
The stock market is known for its extreme complexity and volatility, and people are always looking for an accurate and effective way to guide stock trading. Long short-term memory (LSTM) neural networks are developed by recurrent neural networks (RNN...

Pythagorean 2-Tuple Linguistic Taxonomy Method for Supplier Selection in Medical Instrument Industries.

International journal of environmental research and public health
Supplier selection in medical instrument industries is a classical multiple attribute group decision making (MAGDM) problem. The Pythagorean 2-tuple linguistic sets (P2TLSs) can reflect uncertain or fuzzy information well and solve the supplier selec...

Deep architectures for long-term stock price prediction with a heuristic-based strategy for trading simulations.

PloS one
Stock price prediction is a popular yet challenging task and deep learning provides the means to conduct the mining for the different patterns that trigger its dynamic movement. In this paper, the task is to predict the close price for 25 companies e...

Spatial-temporal variation characteristics and evolution of the global industrial robot trade: A complex network analysis.

PloS one
Industrial robots are a strategic future technology and an important part of the development of artificial intelligence, and they are a necessary means for the intelligent transformation of manufacturing industry. Based on global industrial robot tra...

Alcohol outlets and firearm violence: a place-based case-control study using satellite imagery and machine learning.

Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention
INTRODUCTION: This article proposes a novel method for matching places based on visual similarity, using high-resolution satellite imagery and machine learning. This approach strengthens comparisons when the built environment is a potential confounde...

Can we predict firms' innovativeness? The identification of innovation performers in an Italian region through a supervised learning approach.

PloS one
The study shows the feasibility of predicting firms' expenditures in innovation, as reported in the Community Innovation Survey, applying a supervised machine-learning approach on a sample of Italian firms. Using an integrated dataset of administrati...

Do street-level scene perceptions affect housing prices in Chinese megacities? An analysis using open access datasets and deep learning.

PloS one
Many studies have explored the relationship between housing prices and environmental characteristics using the hedonic price model (HPM). However, few studies have deeply examined the impact of scene perception near residential units on housing price...

Predicting nationwide obesity from food sales using machine learning.

Health informatics journal
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 ...

A New Approach for Construction of Geodemographic Segmentation Model and Prediction Analysis.

Computational intelligence and neuroscience
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...

Forecasting stock prices with a feature fusion LSTM-CNN model using different representations of the same data.

PloS one
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...