AIMC Topic: Forecasting

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Optimal Task Allocation Algorithm Based on Queueing Theory for Future Internet Application in Mobile Edge Computing Platform.

Sensors (Basel, Switzerland)
For 5G and future Internet, in this paper, we propose a task allocation method for future Internet application to reduce the total latency in a mobile edge computing (MEC) platform with three types of servers: a dedicated MEC server, a shared MEC ser...

Forecasting Subway Passenger Flow for Station-Level Service Supply.

Big data
Demand forecasting is one of the managers' concerns in service supply chain management. With accurate passenger flow forecasting, the station-level service suppliers can make better service plans accordingly. However, the existing forecasting model c...

5G Traffic Prediction Based on Deep Learning.

Computational intelligence and neuroscience
The demand of wireless access users is increasing explosively. The 5G network traffic is increasing exponentially and showing a trend of diversity and heterogeneity, which makes network traffic forecasting face many challenges. By studying the actual...

Prospects and Challenges of Using Machine Learning for Academic Forecasting.

Computational intelligence and neuroscience
The study examines the prospects and challenges of machine learning (ML) applications in academic forecasting. Predicting academic activities through machine learning algorithms presents an enhanced means to accurately forecast academic events, inclu...

China's GDP forecasting using Long Short Term Memory Recurrent Neural Network and Hidden Markov Model.

PloS one
This paper presents a Long Short Term Memory Recurrent Neural Network and Hidden Markov Model (LSTM-HMM) to predict China's Gross Domestic Product (GDP) fluctuation state within a rolling time window. We compare the predictive power of LSTM-HMM with ...

Road Traffic Forecast Based on Meteorological Information through Deep Learning Methods.

Sensors (Basel, Switzerland)
Forecasting road flow has strong importance for both allowing authorities to guarantee safety conditions and traffic efficiency, as well as for road users to be able to plan their trips according to space and road occupation. In a summer resort, such...

Deep learning models for forecasting dengue fever based on climate data in Vietnam.

PLoS neglected tropical diseases
BACKGROUND: Dengue fever (DF) represents a significant health burden in Vietnam, which is forecast to worsen under climate change. The development of an early-warning system for DF has been selected as a prioritised health adaptation measure to clima...

Hyperparameter Optimization of Bayesian Neural Network Using Bayesian Optimization and Intelligent Feature Engineering for Load Forecasting.

Sensors (Basel, Switzerland)
This paper proposes a new hybrid framework for short-term load forecasting (STLF) by combining the Feature Engineering (FE) and Bayesian Optimization (BO) algorithms with a Bayesian Neural Network (BNN). The FE module comprises feature selection and ...

The power to harm: AI assistants pave the way to unethical behavior.

Current opinion in psychology
Advances in artificial intelligence (AI) enable new ways of exercising and experiencing power by automating interpersonal tasks such as interviewing and hiring workers, managing and evaluating work, setting compensation, and negotiating deals. As the...