Search Results

How Boltzmann Entropy Improves Prediction with LSTM,
Luca Grilli and Domenico Santoro, from University Library of Munich, Germany (2020)
Keywords: Neural Network; Price Forecasting; LSTM; Entropy

LSTM-Based Neural Network Model for Semantic Search,
Xiaoyu Guo, Jing Ma and Xiaofeng Li, from Springer (2020)
Keywords: LSTM, Deep learning, Semantic search, RNN

LSTM–GARCH Hybrid Model for the Prediction of Volatility in Cryptocurrency Portfolios,
Andrés García-Medina and Ester Aguayo-Moreno, in Computational Economics (2024)
Keywords: Cryptocurrencies, GARCH–LSTM models, Volatility

A Comparative Analysis of the ARIMA and LSTM Predictive Models and Their Effectiveness for Predicting Wind Speed,
Meftah Elsaraiti and Adel Merabet, in Energies (2021)
Keywords: ARIMA; forecasting; LSTM; wind speed

HP-LSTM: Hawkes Process–LSTM-Based Detection of DDoS Attack for In-Vehicle Network,
Xingyu Li, Ruifeng Li and Yanchen Liu, in Future Internet (2024)
Keywords: Hawkes process; LSTM; DDoS; SOME/IP

Prévision de l’inflation en Côte D’ivoire: Analyse Comparée des Modèles Arima, Holt-Winters, et Lstm,
Siméon Koffi, from University Library of Munich, Germany (2022)
Keywords: LSTM, ARIMA, HOLT-WINTERS

SCE-LSTM: Sparse Critical Event-Driven LSTM Model with Selective Memorization for Agricultural Time-Series Prediction,
Ga-Ae Ryu, Tserenpurev Chuluunsaikhan, Aziz Nasridinov, HyungChul Rah and Kwan-Hee Yoo, in Agriculture (2023)
Keywords: sparse critical event-driven LSTM (SCE-LSTM); forecasting; pork consumption; unstructured big data

Predictions for COVID-19 with deep learning models of LSTM, GRU and Bi-LSTM,
Farah Shahid, Aneela Zameer and Muhammad Muneeb, in Chaos, Solitons & Fractals (2020)
Keywords: Deep learning models; Bi-LSTM; GRU; Corona virus; COVID-19; epidemic prediction;

LSTM-Based Coherent Mortality Forecasting for Developing Countries,
Jose Garrido, Yuxiang Shang and Ran Xu, in Risks (2024)
Keywords: coherent mortality forecasting; LSTM; developing countries; life expectancy; lifespan disparity

Commercial Vacancy Prediction Using LSTM Neural Networks,
Jaekyung Lee, Hyunwoo Kim and Hyungkyoo Kim, in Sustainability (2021)
Keywords: commercial vacancy; LSTM; time-series forecasting; spatial big data

MACLA-LSTM: A Novel Approach for Forecasting Water Demand,
Ke Wang, Zanting Ye, Zhangquan Wang, Banteng Liu and Tianheng Feng, in Sustainability (2023)
Keywords: CLA; LSTM; urban water supply; water demand forecasting

Green Roof Hydrological Modelling With GRU and LSTM Networks,
Haowen Xie, Mark Randall and Kwok-wing Chau, in Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) (2022)
Keywords: Green Roof, Machine Learning, LSTM, GRU, Hydrologic Modelling

Deep Learning Peephole LSTM Neural Network-Based Channel State Estimators for OFDM 5G and Beyond Networks,
Mohamed Hassan Essai Ali, Ali R. Abdellah, Hany A. Atallah, Gehad Safwat Ahmed, Ammar Muthanna and Andrey Koucheryavy, in Mathematics (2023)
Keywords: LSTM; peephole LSTM; GRU; deep learning; channel estimation

Electrical Load Forecast by Means of LSTM: The Impact of Data Quality,
Alfredo Nespoli, Emanuele Ogliari, Silvia Pretto, Michele Gavazzeni, Sonia Vigani and Franco Paccanelli, in Forecasting (2021)
Keywords: load forecast; outliers detection; LSTM; machine learning

System load trend prediction method based on IF-EMD-LSTM,
Jing Yu, Feng Ding, Chenghao Guo and Yabin Wang, in International Journal of Distributed Sensor Networks (2019)
Keywords: System load trend; isolated forests; EMD; LSTM

Comparison of ARIMA and LSTM in Predicting Structural Deformation of Tunnels during Operation Period,
Chuangfeng Duan, Min Hu and Haozuan Zhang, in Data (2023)
Keywords: tunnel; structural deformation; ARIMA; LSTM; prediction

Prediction Model of Ammonia Nitrogen Concentration in Aquaculture Based on Improved AdaBoost and LSTM,
Yiyang Wang, Dehao Xu, Xianpeng Li and Wei Wang, in Mathematics (2024)
Keywords: aquaculture; adaptive boosting algorithm; LSTM; combined prediction

A Novel Variant of LSTM Stock Prediction Method Incorporating Attention Mechanism,
Shuai Sang and Lu Li, in Mathematics (2024)
Keywords: LSTM; attention mechanism; stock price prediction

Comparing ChatGPT and LSTM in predicting changes in quarterly financial metrics,
Vitali Chaiko, in Business & Management Compass (2024)
Keywords: ChatGPT, financial metrics prediction, LSTM, twitter

Estimación adelantada del crecimiento regional mediante redes neuronales LSTM,
Juan de Lucio, in INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH (2021)
Keywords: regional analysis; neural networks; artificial intelligence; LSTM

LSTM forecasting foreign exchange rates using limit order book,
Katsuki Ito, Hitoshi Iima and Yoshihiro Kitamura, in Finance Research Letters (2022)
Keywords: foreign exchange rate; limit order; LSTM;

A hybrid transformer-based BERT and LSTM approach for vulnerability classification problems,
Mounesh Marali, R. Dhanalakshmi and Narendran Rajagopalan, in International Journal of Mathematics in Operational Research (2024)
Keywords: vulnerability; classification; LSTM; BERT; cyber threat intelligence.

LSTM Networks to Improve the Prediction of Harmful Algal Blooms in the West Coast of Sabah,
Fatin Nadiah Yussof, Normah Maan and Mohd Nadzri Md Reba, in IJERPH (2021)
Keywords: chlorophyll a ; CNN; LSTM; prediction; satellite data

A Novel Bézier LSTM Model: A Case Study in Corn Analysis,
Qingliang Zhao, Junji Chen, Xiaobin Feng and Yiduo Wang, in Mathematics (2024)
Keywords: price forecast; LSTM; Bézier curve; ARIMA; SVR

A Hybrid ARIMA-LSTM Model for Short-Term Vehicle Speed Prediction,
Wei Wang, Bin Ma, Xing Guo, Yong Chen and Yonghong Xu, in Energies (2024)
Keywords: speed prediction; hybrid model; ARIMA; LSTM; nonlinear

Effects of Training Data on the Learning Performance of LSTM Network for Runoff Simulation,
Anbang Peng, Xiaoli Zhang, Wei Xu and Yuanyang Tian, in Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) (2022)
Keywords: LSTM, Rainfall runoff, Data amount, Over-fitting

Simulation of Urban Flood Process Based on a Hybrid LSTM-SWMM Model,
Chenchen Zhao, Chengshuai Liu, Wenzhong Li, Yehai Tang, Fan Yang, Yingying Xu, Liyu Quan and Caihong Hu, in Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) (2023)
Keywords: LSTM, SWMM, Urban Flood, Hydrologic elements

Streamflow forecasting using a hybrid LSTM-PSO approach: the case of Seyhan Basin,
Bulent Haznedar, Huseyin Cagan Kilinc, Furkan Ozkan and Adem Yurtsever, in Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards (2023)
Keywords: Forecasting, Streamflow, ANFIS, LSTM, PSO, Time Series

ERFLSTM: Enhanced regularization function in LSTM to assess feature importance,
Usharani Bhimavarapu, in International Journal of System Assurance Engineering and Management (2024)
Keywords: Feature importance, LSTM, Regularization, Standard deviation

On the use of VMD-LSTM neural network for approximate earthquake prediction,
Qiyue Wang, Yekun Zhang, Jiaqi Zhang, Zekang Zhao and Xijun He, in Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards (2024)
Keywords: Earthquake prediction, LSTM, VMD, Deep learning

Forecasting Stock Price Index Volatility with LSTM Deep Neural Network,
ShuiLing Yu and Zhe Li, from Springer (2018)
Keywords: LSTM, Volatility forecasting, Extreme value volatility, GARCH

Forecasting of Photovoltaic Solar Power Production Using LSTM Approach,
Fouzi Harrou and Farid Kadri, from IntechOpen
Keywords: forecasting, deep learning, LSTM, solar power production

Photovoltaic power forecasting based LSTM-Convolutional Network,
Kejun Wang, Xiaoxia Qi and Hongda Liu, in Energy (2019)
Keywords: Photovoltaic power forecasting; Convolutional neural network; Long-short term memory; LSTM-Convolutional network; Convolutional-LSTM network; Deep learning;

Forecasting Detrended Volatility Risk and Financial Price Series Using LSTM Neural Networks and XGBoost Regressor,
Aistis Raudys and Edvinas Goldstein, in JRFM (2022)
Keywords: returns; detrending; LSTM; trading strategies

LSTM-AE-WLDL: Unsupervised LSTM Auto-Encoders for Leak Detection and Location in Water Distribution Networks,
Maryam Kammoun, Amina Kammoun and Mohamed Abid, in Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) (2023)
Keywords: Leak detection, Leak area location, Unsupervised RNN, LSTM autoencoder, LeakDB

A Novel NODE Approach Combined with LSTM for Short-Term Electricity Load Forecasting,
Songtao Huang, Jun Shen, Qingquan Lv, Qingguo Zhou and Binbin Yong, in Future Internet (2022)
Keywords: neural ordinary differential equation; LSTM; bidirectional LSTM; short-term load forecasting

Prediction of Gas Concentration Based on LSTM-LightGBM Variable Weight Combination Model,
Xiangqian Wang, Ningke Xu, Xiangrui Meng and Haoqian Chang, in Energies (2022)
Keywords: coal mine safety; LSTM; LightGBM; LSTM-LightGBM variable weight combination; gas concentration prediction

Enhancing continuous time series modelling with a latent ODE-LSTM approach,
C. Coelho, M. Fernanda P. Costa and L.L. Ferrás, in Applied Mathematics and Computation (2024)
Keywords: Machine learning; Neural ODE; Latent ODE; RNN; LSTM; Latent ODE-LSTM; Gradient clipping;

Investigation of Bi-Directional LSTM deep learning-based ubiquitous MIMO uplink NOMA detection for military application considering Robust channel conditions,
Joel Alanya-Beltran, Ravi Shankar, Patteti Krishna and Selva Kumar S, in The Journal of Defense Modeling and Simulation (2023)
Keywords: MIMO; NOMA; 5G; LSTM; SIC

DEEP QUALITY-CONSTRAINED LSTM FOR TEXTUAL DATA ANALYSIS,
Linyu Li and Xiaoyu Luo, in FRACTALS (fractals) (2022)
Keywords: Machine Learning, Textual Data Analysis, Attention Mechanism, LSTM Network, Natural Language Processing

Landslide Displacement Prediction Based on Multivariate LSTM Model,
Gonghao Duan, Yangwei Su and Jie Fu, in IJERPH (2023)
Keywords: landslide; displacement prediction; cubic spline interpolation; multivariate LSTM; Three Gorges Reservoir area

LSTM-Based Forecasting for Urban Construction Waste Generation,
Li Huang, Ting Cai, Ya Zhu, Yuliang Zhu, Wei Wang and Kehua Sun, in Sustainability (2020)
Keywords: environmental engineering; construction waste; short and long-term memory (LSTM) network; time-series forecasting; deep learning

Anomaly Detection in Fractal Time Series with LSTM Autoencoders,
Lyudmyla Kirichenko, Yulia Koval, Sergiy Yakovlev and Dmytro Chumachenko, in Mathematics (2024)
Keywords: anomaly detection; Hurst exponent; fractal Brownian motion; machine learning; LSTM autoencoder

Forecasting Brazilian Ethanol Spot Prices Using LSTM,
Gustavo Carvalho Santos, Flavio Barboza, Antônio Cláudio Paschoarelli Veiga and Mateus Ferreira Silva, in Energies (2021)
Keywords: price prediction; trend prediction; LSTM; SVM; Random Forest; MAPE; MSE; commodity price

LSTM-ARIMA as a Hybrid Approach in Algorithmic Investment Strategies,
Kamil Kashif and Robert Ślepaczuk, from Faculty of Economic Sciences, University of Warsaw (2024)
Keywords: Deep Learning, Recurrent Neural Networks, Algorithmic Investment Strategy, LSTM, ARIMA, Hybrid/Ensemble Models, Walk-Forward Process

Forward-Looking Element Recognition Based on the LSTM-CRF Model with the Integrity Algorithm,
Dong Xu, Ruping Ge and Zhihua Niu, in Future Internet (2019)
Keywords: LSTM-CRF model; elements recognition; linguistic features; POS syntactic rules

Roll Motion Prediction of Unmanned Surface Vehicle Based on Coupled CNN and LSTM,
Wenjie Zhang, Pin Wu, Yan Peng and Dongke Liu, in Future Internet (2019)
Keywords: CNN; data-driven; LSTM; roll motion prediction; unmanned surface vehicle

A Hybrid CNN-LSTM Model for SMS Spam Detection in Arabic and English Messages,
Abdallah Ghourabi, Mahmood A. Mahmood and Qusay M. Alzubi, in Future Internet (2020)
Keywords: SMS spam detection; deep learning; CNN; LSTM; SMS Classification

Forecasting Sales in the Supply Chain Based on the LSTM Network: The Case of Furniture Industry,
Damian Pliszczuk, Piotr Lesiak, Krzysztof Zuk and Tomasz Cieplak, in European Research Studies Journal (2021)
Keywords: Machine learning, time series, LSTM, supply chain, forecasting.

Forecasting the Traffic Flow by Using ARIMA and LSTM Models: Case of Muhima Junction,
Vienna N. Katambire, Richard Musabe, Alfred Uwitonze and Didacienne Mukanyiligira, in Forecasting (2023)
Keywords: ARIMA; LSTM; traffic flow; ITS; forecasting; Internet of Things; traffic management

LSTM based Anomaly Detection in Time Series for United States exports and imports,
Sakshi Aggarwal, from University Library of Munich, Germany (2023)
Keywords: Anomaly detection, LSTM, Machine learning, Artificial intelligence, economic trade

DSM pricing method based on A3C and LSTM under cloud-edge environment,
Fangyuan Sun, Xiangyu Kong, Jianzhong Wu, Bixuan Gao, Ke Chen and Ning Lu, in Applied Energy (2022)
Keywords: Demand-side management; LSTM; A3C; Cloud-edge environment;

Well production forecasting based on ARIMA-LSTM model considering manual operations,
Dongyan Fan, Hai Sun, Jun Yao, Kai Zhang, Xia Yan and Zhixue Sun, in Energy (2021)
Keywords: Production forecasting; Hybrid model; ARIMA; LSTM; Daily production time series;

Forecasting power demand in China with a CNN-LSTM model including multimodal information,
Delu Wang, Jun Gan, Jinqi Mao, Fan Chen and Lan Yu, in Energy (2023)
Keywords: Power demand; Forecasting; Multimodal information fusion; Feature fusion; CNN-LSTM;

Risk Evaluation Model of Coal Spontaneous Combustion Based on AEM-AHP-LSTM,
Xu Zhou, Shangsheng Ren, Shuo Zhang, Jiuling Zhang and Yibo Wang, in Mathematics (2022)
Keywords: coal spontaneous combustion; risk evaluation; AEM; AHP; LSTM; mine intelligence

Prediction of COVID-19 Data Using an ARIMA-LSTM Hybrid Forecast Model,
Yongchao Jin, Renfang Wang, Xiaodie Zhuang, Kenan Wang, Honglian Wang, Chenxi Wang and Xiyin Wang, in Mathematics (2022)
Keywords: ARIMA; LSTM; SVR; linear regression; number of cases forecast

LSTM-Based Stacked Autoencoders for Early Anomaly Detection in Induction Heating Systems,
Mohammed H. Qais, Seema Kewat, Ka Hong Loo, Cheung-Ming Lai and Aldous Leung, in Mathematics (2023)
Keywords: anomaly detection; autoencoder; deep learning; induction heating system; LSTM

A Novel Prediction Model for Seawall Deformation Based on CPSO-WNN-LSTM,
Sen Zheng, Chongshi Gu, Chenfei Shao, Yating Hu, Yanxin Xu and Xiaoyu Huang, in Mathematics (2023)
Keywords: seawall; deformation prediction model; influencing factors determination; CPSO; WNN; LSTM

Optimization Hybrid of Multiple-Lag LSTM Networks for Meteorological Prediction,
Lin Zhu, Zhihua Zhang, M. James C. Crabbe and Lipon Chandra Das, in Mathematics (2023)
Keywords: multiple-lag LSTM networks; optimization hybrid; meteorological prediction

LSTM-augmented deep networks for time-variant reliability assessment of dynamic systems,
Mingyang Li and Zequn Wang, in Reliability Engineering and System Safety (2022)
Keywords: LSTM; dynamic systems; time-variant reliability; deep learning; Gaussian Process;

Value-at-Risk forecasting: A hybrid ensemble learning GARCH-LSTM based approach,
Kshitij Kakade, Ishan Jain and Aswini Kumar Mishra, in Resources Policy (2022)
Keywords: Value-at-Risk; BiLSTM; LSTM; GARCH; Ensemble; Crude oil;

Encoder–Decoder Based LSTM and GRU Architectures for Stocks and Cryptocurrency Prediction,
Joy Dip Das, Ruppa K. Thulasiram, Christopher Henry and Aerambamoorthy Thavaneswaran, in JRFM (2024)
Keywords: autoencoder; LSTM; GRU; hybridization; stocks; stock index; cryptocurrency

Cucumber Downy Mildew Disease Prediction Using a CNN-LSTM Approach,
Yafei Wang, Tiezhu Li, Tianhua Chen, Xiaodong Zhang, Mohamed Farag Taha, Ning Yang, Hanping Mao and Qiang Shi, in Agriculture (2024)
Keywords: greenhouse; cucumber downy mildew; CNN-LSTM; prediction model

An Approach for Fall Prediction Based on Kinematics of Body Key Points Using LSTM,
Bahareh Mobasheri, Seyed Reza Kamel Tabbakh and Yahya Forghani, in IJERPH (2022)
Keywords: falls prediction; older adults; health promotion; wellness; LSTM; image processing

Direct Prediction of the Toxic Gas Diffusion Rule in a Real Environment Based on LSTM,
Fei Qian, Li Chen, Jun Li, Chao Ding, Xianfu Chen and Jian Wang, in IJERPH (2019)
Keywords: toxic gas; diffusion prediction models; deep learning algorithms; LSTM

Updated Prediction of Air Quality Based on Kalman-Attention-LSTM Network,
Hao Zhou, Tao Wang, Hongchao Zhao and Zicheng Wang, in Sustainability (2022)
Keywords: second prediction; AQI; Kalman filter; Kalman-attention-LSTM

Macroeconomic Forecasting with LSTM and Mixed Frequency Time Series Data,
Sarun Kamolthip, from Puey Ungphakorn Institute for Economic Research (2021)
Keywords: LSTM; Mixed Frequency Data; Nowcasting; Time Series; Macroeconomic Indicators

Prophet-LSTM-BP Ensemble Carbon Trading Price Prediction Model,
Fansheng Meng and Rong Dou, in Computational Economics (2024)
Keywords: Prophet, LSTM, Carbon trading price predict, Ensemble learning Model

Short-Term Forecast of Photovoltaic Solar Energy Production Using LSTM,
Filipe D. Campos, Tiago C. Sousa and Ramiro S. Barbosa, in Energies (2024)
Keywords: short-term forecasting; LSTM; solar energy production; ANN; CNN

Predicting the Remaining Life of Centrifugal Pump Bearings Using the KPCA–LSTM Algorithm,
Rongsheng Zhu, Xinyu Zhang, Qian Huang, Sihan Li and Qiang Fu, in Energies (2024)
Keywords: centrifugal pump; rolling bearing; life prediction; feature fusion; KPCA; LSTM

A Forecasting Model of Wind Power Based on IPSO–LSTM and Classified Fusion,
Qiuhong Huang and Xiao Wang, in Energies (2022)
Keywords: IPSO; LSTM; wind power forecast; classification of the fusion pattern; data fusion

Lithologic Identification of Complex Reservoir Based on PSO-LSTM-FCN Algorithm,
Yawen He, Weirong Li, Zhenzhen Dong, Tianyang Zhang, Qianqian Shi, Linjun Wang, Lei Wu, Shihao Qian, Zhengbo Wang, Zhaoxia Liu and Gang Lei, in Energies (2023)
Keywords: complex reservoir; lithology identification; machine learning; LSTM-FCN; PSO optimization

Generating Occupancy Profiles for Building Simulations Using a Hybrid GNN and LSTM Framework,
Yuan Xie and Spyridon Stravoravdis, in Energies (2023)
Keywords: occupancy; energy simulation; neural networks; GNN; LSTM; RNN; GRU; RNN

A Context-Aware Location Recommendation System for Tourists Using Hierarchical LSTM Model,
Wafa Shafqat and Yung-Cheol Byun, in Sustainability (2020)
Keywords: context aware; recommendation system; LSTM; feature importance; XGBoost; tourism

Comparing LSTM and GRU Models to Predict the Condition of a Pulp Paper Press,
Balduíno César Mateus, Mateus Mendes, José Torres Farinha, Rui Assis and António Marques Cardoso, in Energies (2021)
Keywords: LSTM; recurrent neural network; GRU; paper press; predictive maintenance

Forecasting of Natural Gas Consumption in Poland Based on ARIMA-LSTM Hybrid Model,
Anna Manowska, Aurelia Rybak, Artur Dylong and Joachim Pielot, in Energies (2021)
Keywords: natural gas consumption; natural gas trade; energy markets; ARIMA; LSTM

A Hybrid Channel-Communication-Enabled CNN-LSTM Model for Electricity Load Forecasting,
Faisal Saeed, Anand Paul and Hyuncheol Seo, in Energies (2022)
Keywords: cross-channel communication; Convolutional Neural Networks; LSTM; electricity; load; forecasting

Research on Gas Concentration Prediction Models Based on LSTM Multidimensional Time Series,
Tianjun Zhang, Shuang Song, Shugang Li, Li Ma, Shaobo Pan and Liyun Han, in Energies (2019)
Keywords: coal mine safety; recurrent neural network; deep learning; LSTM regression

Bus Schedule Time Prediction Based on LSTM-SVR Model,
Zhili Ge, Linbo Yang, Jiayao Li, Yuan Chen and Yingying Xu, in Mathematics (2024)
Keywords: bus schedule time; prediction; deep learning; LSTM-SVR

Optimization of LSTM Parameters for Flash Flood Forecasting Using Genetic Algorithm,
You-Da Jhong, Chang-Shian Chen, Bing-Chen Jhong, Cheng-Han Tsai and Song-Yue Yang, in Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) (2024)
Keywords: Flood, LSTM, GA, Time window, Hidden layer, Hidden neuron

Prediction of consumer repurchase behavior based on LSTM neural network model,
Chuzhi Zhu, Minzhi Wang and Chenghao Su, in International Journal of System Assurance Engineering and Management (2022)
Keywords: Edge computing, LSTM neural network, Deep learning, Behavior prediction

Forecasting directional movement of Forex data using LSTM with technical and macroeconomic indicators,
Deniz Can Yıldırım, Ismail Hakkı Toroslu and Ugo Fiore, in Financial Innovation (2021)
Keywords: Time series, Forex, Directional movement forecasting, Technical and macroeconomic indicators, LSTM

Positioning of logistics and warehousing automated guided vehicle based on improved LSTM network,
Tingting Yan, in International Journal of System Assurance Engineering and Management (2023)
Keywords: LSTM network, Logistics warehousing, Automatic guided vehicle, Positioning analysis

Hydropower Station Status Prediction Using RNN and LSTM Algorithms for Fault Detection,
Omar Farhan Al-Hardanee and Hüseyin Demirel, in Energies (2024)
Keywords: RNN; LSTM; forecasting; vibration; temperature; pressure; turbine; dam

FDNet: Frequency filter enhanced dual LSTM network for wind power forecasting,
Yipeng Mo, Haoxin Wang, Chengteng Yang, Zuhua Yao, Bixiong Li, Songhai Fan and Site Mo, in Energy (2024)
Keywords: Wind power forecasting; Patching operation; Frequency filter; Dual LSTM;

Forecasting the Monkeypox Outbreak Using ARIMA, Prophet, NeuralProphet, and LSTM Models in the United States,
Bowen Long, Fangya Tan and Mark Newman, in Forecasting (2023)
Keywords: Monkeypox; forecasting; ARIMA; LSTM; Prophet; NeuralProphet

Task Offloading Based on LSTM Prediction and Deep Reinforcement Learning for Efficient Edge Computing in IoT,
Youpeng Tu, Haiming Chen, Linjie Yan and Xinyan Zhou, in Future Internet (2022)
Keywords: computational offloading; resource allocation; prediction; DRL; LSTM

Comparative analysis and forecasting of COVID-19 cases in various European countries with ARIMA, NARNN and LSTM approaches,
İsmail Kırbaş, Adnan Sözen, Azim Doğuş Tuncer and Fikret Şinasi Kazancıoğlu, in Chaos, Solitons & Fractals (2020)
Keywords: COVID-19; Forecasting; ARIMA; NARNN; LSTM; Modeling;

Meta-Heuristic Optimization of LSTM-Based Deep Network for Boosting the Prediction of Monkeypox Cases,
Marwa M. Eid, El-Sayed M. El-Kenawy, Nima Khodadadi, Seyedali Mirjalili, Ehsaneh Khodadadi, Mostafa Abotaleb, Amal H. Alharbi, Abdelaziz A. Abdelhamid, Abdelhameed Ibrahim, Ghada M. Amer, Ammar Kadi and Doaa Sami Khafaga, in Mathematics (2022)
Keywords: monkeypox; meta-heuristic optimization; LSTM; deep learning

Short-term global horizontal irradiance forecasting based on a hybrid CNN-LSTM model with spatiotemporal correlations,
Haixiang Zang, Ling Liu, Li Sun, Lilin Cheng, Zhinong Wei and Guoqiang Sun, in Renewable Energy (2020)
Keywords: Solar irradiance; CNN; LSTM; Spatiotemporal correlation;