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Wavelet-SARIMA-Transformer: a hybrid model for rainfall forecasting

Theoretical and Applied Climatology
Rainfall forecasting in monsoon-dominated regions is challenging due to the nonlinear, nonstationary, and scale-dependent nature of precipitation dynamics.
Junmoni Saikia   +2 more
semanticscholar   +1 more source

Improving time series forecasting using LSTM and attention models

Journal of Ambient Intelligence and Humanized Computing, 2021
H. Abbasimehr, Reza Paki
semanticscholar   +1 more source

Deep Learning-Based Vehicular Millimeter-Wave Channel Prediction Using Visual Information

IEEE Antennas and Wireless Propagation Letters
Millimeter-wave channel prediction requires detailed and accurate environmental information due to the challenges of non-line-of-sight transmission and severe reflection and scattering.
Shirui Wang   +8 more
semanticscholar   +1 more source

Dynamic Scheduling and Islanding Energy Management in Microgrids using Deep Learning and Adaptive Reinforcement Learning Techniques

International Conferences on Information Science and System
The increasing reliance on renewable energy resources has introduced significant challenges in microgrid energy management, particularly during islanding conditions.
M. Ramya, T. Devaraju
semanticscholar   +1 more source

RiskAwareTNet: A Multi-Task Deep Learning Framework for Stock Price Prediction and Risk Assessment

European Conference on Cognitive Ergonomics
This paper introduces RiskAwareTNet, a novel deep-learning model designed for multi-task learning that addresses stock price prediction and risk evaluation.
Afsana Alam Nova   +5 more
semanticscholar   +1 more source

Free Cash Flow Prediction of Companies on IDX30 Index on Indonesia Stock Exchanges Using Light Gradient Boosting Machine (LGBM) Method

2025 3rd International Conference on Software Engineering and Information Technology (ICoSEIT)
Predicting free cash flow is vital task for estimating a company’s future financial outlook and supporting informed investment decisions. This study employs Light Gradient Boosting Machine (LGBM) to forecast FCF.
Dhiaurizqi Ramadhani Sanusi, D. Saepudin
semanticscholar   +1 more source

Optimum design of a novel plasmonic absorber-based material sensor using metaheuristic algorithm

Physica Scripta
This paper presents a miniaturized plasmonic absorber-based material sensor operating at 0.8 THz, designed using a multilayer graphene-polyimide structure.
G. Ananthakrishnan   +2 more
semanticscholar   +1 more source

Time to Revist Exact Match

Conference on Empirical Methods in Natural Language Processing
Temporal question answering is an established method for evaluating temporal reasoning in large language models. Expected answers are often numeric (e.g., dates or durations), yet model responses are evaluated like regular text with exact match (EM ...
Auss Abbood, Zaiqiao Meng, Nigel Collier
semanticscholar   +1 more source

An Integrated LSTM-TabNet Ensemble with Elastic Net for Jakarta Composite Index Forecasting

2025 1st International Conference on Emerging Trends in Information Systems and Informatics (ICETISI)
Forecasting the Jakarta Composite Index (IHSG) remains challenging due to its high sensitivity to global financial dynamics and nonlinear market interactions.
Muhammad Rangga Miftahul Falah   +3 more
semanticscholar   +1 more source

Mathematical Modelling of Remote Sensing Time Series: A Case Study of Hurst Castle

WSEAS Transactions on Environment and Development
This study presents a multi-temporal analysis of displacement data from Sentinel-1 Synthetic Aperture Radar data at Hurst Castle with datasets sourced from the European Ground Motion Service, and temperature records from Ventnor Park and Otterbourne ...
Anastasia Sofroniou   +3 more
semanticscholar   +1 more source

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