Results 121 to 130 of about 127,689 (298)

Intelligent short-term load forecasting in Turkey

International Journal of Electrical Power & Energy Systems, 2006
Abstract A method is proposed to forecast Turkey’s total electric load one day in advance by neural networks. A hybrid learning scheme that combines off-line learning with real-time forecasting is developed to use the available data for adapting the weights and to further adjust these connections according to changing conditions.
Ayca Kumluca Topalli, Ismet Erkmen, Ihsan Topalli   +2 more
openaire   +1 more source

A hybrid model of modal decomposition and gated recurrent units for short-term load forecasting. [PDF]

PeerJ Comput Sci, 2023
Wang CH, Li WQ.
europepmc   +1 more source

Remote Monitoring in Myasthenia Gravis: Exploring Symptom Variability

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Myasthenia gravis (MG) is a rare, autoimmune disorder characterized by fluctuating muscle weakness and potential life‐threatening crises. While continuous specialized care is essential, access barriers often delay timely interventions. To address this, we developed MyaLink, a telemedical platform for MG patients.
Maike Stein, Maximilian Mönch, Meret Herdick, Frauke Stascheit, Sarah Hoffmann, Hannah Preßler, Philipp Mergenthaler, Carla Dusemund, Paolo Doksani, Haoqi Sun, Pushpa Narayanaswami, Andreas Meisel, Lea Gerischer, Sophie Lehnerer   +13 more
wiley   +1 more source

Multi-horizon short-term load forecasting using hybrid of LSTM and modified split convolution. [PDF]

PeerJ Comput Sci, 2023
Ullah I, Muhammad Hasanat S, Aurangzeb K, Alhussein M, Rizwan M, Anwar MS.   +5 more
europepmc   +1 more source

Development of a Prediction Model for Progression Risk in High‐Grade Gliomas Based on Habitat Radiomics and Pathomics

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To investigate the value of constructing models based on habitat radiomics and pathomics for predicting the risk of progression in high‐grade gliomas. Methods This study conducted a retrospective analysis of preoperative magnetic resonance (MR) images and pathological sections from 72 patients diagnosed with high‐grade gliomas (52 ...
Yuchen Zhu, Yuxi Gong, Weilin Xu, Xingjian Sun, Gefei Jiang, Lei Qiu, Kexin Shi, Mengxing Wu, Yinjiao Fei, Jinling Yuan, Jinyan Luo, Yurong Li, Yuandong Cao, Minhong Pan, Shu Zhou   +14 more
wiley   +1 more source

Research on Load Forecasting Based on Bayesian Optimized CNN-LSTM Neural Network

Energies
With the high penetration of renewable energy integration and massive user participation in electricity markets, traditional short-term load forecasting methods exhibit limitations in both adaptability and prediction accuracy.
Pengyang Duan, Huannian Jiao, Jianying Sun, Aiming Han, Zheng Dai, Liang Cheng, Xiaotao Chen   +6 more
doaj   +1 more source

Short-term load forecasting system based on sliding fuzzy granulation and equilibrium optimizer. [PDF]

Appl Intell (Dordr), 2023
Li S, Wang J, Zhang H, Liang Y.
europepmc   +1 more source

Stacking for Probabilistic Short-Term Load Forecasting

In this study, we delve into the realm of meta-learning to combine point base forecasts for probabilistic short-term electricity demand forecasting. Our approach encompasses the utilization of quantile linear regression, quantile regression forest, and post-processing techniques involving residual simulation to generate quantile forecasts. Furthermore,
openaire   +2 more sources

Spinal Cord Infarction Versus Idiopathic Transverse Myelitis: Clinical, Radiological, and Functional Insights From a Retrospective Cohort Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Introduction Spinal cord infarction (SCI) is a rare but devastating myelopathy, characterized by a high disability rate and an unfavorable prognosis. It has often been underdiagnosed and misdiagnosed as idiopathic transverse myelitis (ITM). This study aimed to describe the clinical features, radiological biomarkers, treatments, and functional ...
Zeqiang Ji, Jianlong Zhang, Yiming Shi, Shiyu Shan, Yang Du, Guangshuo Li, Ying Jin, Yani Zhang, Chuanying Wang, Yijun Lin, Yuhao Guo, Decai Tian, Xingquan Zhao, Tian Song   +13 more
wiley   +1 more source

Improvement of short-term electric load forecasting using neural networks with preprocessing the load data [PDF]

, 2015
Пропонується інтелектуальна система, на базі штучної нейронної мережі з використанням попередньої підготовки даних, для покращення короткострокового прогнозування навантаження в енергосистемах.
Тишевич, Б. Л.
core