Prediction of Sorption Processes Using the Deep Learning Methods (Long Short-Term Memory)

Effect of Metal and Carbon Nanotube Additives on the Thermal Diffusivity of a Silica Gel-Based Adsorption Bed

(2020) Anna Kulakowska et al.   Energies

Review of Adsorptive Heat Conversion/Storage in Cold Climate Countries

(2020) Yu.I. Aristov   APPLIED THERMAL ENGINEERING

Snowmelt-Driven Streamflow Prediction Using Machine Learning Techniques (LSTM, NARX, GPR, and SVR)

(2020) Samit Thapa et al.   Water

Comparative analysis and forecasting of COVID-19 cases in various European countries with ARIMA, NARNN and LSTM approaches

(2020) İsmail Kırbaş et al.   CHAOS SOLITONS & FRACTALS

Construction of an innovative adsorbent bed configuration in the adsorption chiller part 2. experimental research of coated bed samples

(2020) K. Grabowska et al.   ENERGY

Application of deep neural techniques in predictive modeling for the estimation of Escherichia coli growth rate

(2020) M. Chitra et al.   JOURNAL OF APPLIED MICROBIOLOGY

Deep Recurrent Entropy Adaptive Model for System Reliability Monitoring

(2020) Miguel Martinez-Garcia et al.   IEEE Transactions on Industrial Informatics

Data processing strategies in wind energy forecasting models and applications: A comprehensive review

(2019) Hui Liu et al.   APPLIED ENERGY

Modeling the performance of a sorption thermal energy storage reactor using artificial neural networks

(2019) Luca Scapino et al.   APPLIED ENERGY

A General Approach in Optimization of Heat Exchangers by Bio-Inspired Artificial Intelligence Methods

(2019) Jaroslaw Krzywanski   Energies

Memory Pattern Identification for Feedback Tracking Control in Human–Machine Systems

(2019) Miguel Martínez-García et al.   HUMAN FACTORS

Evaluation of Heat Transfer Performance of a Multi-Disc Sorption Bed Dedicated for Adsorption Cooling Technology

(2019) Marcin Sosnowski   Energies

Construction of an innovative adsorbent bed configuration in the adsorption chiller - Selection criteria for effective sorbent-glue pair

(2018) Karolina Grabowska et al.   ENERGY

Genetic algorithms and neural networks in optimization of sorbent enhanced H 2 production in FB and CFB gasifiers

(2018) Jaroslaw Krzywanski et al.   ENERGY CONVERSION AND MANAGEMENT

Optimization of a three-bed adsorption chiller by genetic algorithms and neural networks

(2017) J. Krzywanski et al.   ENERGY CONVERSION AND MANAGEMENT

LSTM network: a deep learning approach for short-term traffic forecast

(2017) Zheng Zhao et al.   IET Intelligent Transport Systems

A 1.5D model of a complex geometry laboratory scale fuidized bed clc equipment

(2017) J. Krzywanski et al.   POWDER TECHNOLOGY

Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks

(2017) Haiyang Yu et al.   SENSORS

Modelling and experimental investigation of an adsorption chiller using low-temperature heat from cogeneration

(2015) Maciej Chorowski et al.   ENERGY

Thermo-ecological assessment of CCHP (combined cold-heat-and-power) plant supported with renewable energy

(2015) Wojciech Stanek et al.   ENERGY

Deep learning

(2015) Yann LeCun et al.   NATURE

Long short-term memory neural network for traffic speed prediction using remote microwave sensor data

(2015) Xiaolei Ma et al.   TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES

Exergo-ecological evaluation of adsorption chiller system

(2014) Wojciech Stanek et al.   ENERGY

Optimization of adsorption dynamics in adsorptive chillers: Loose grains configuration

(2012) Yuriy I. Aristov et al.   ENERGY