The adoption of contemporary techniques to boost agricultural output is unavoidable given worries about the growth of the world's population and the scarcity of food. Artificial neural networks (ANN) in particular...
详细信息
this paper investigates the potential of using time collection evaluation to detect Merkel cellular Carcinoma (MCC) early. MCC is a competitive shape of pores and skin. Early detection is critical to the growing survi...
详细信息
In contrast to the single intelligent reflecting surface (S-IRS) systems, improved performance is attainable by employing double-IRS (D-IRS) in a wireless-communication system. Nevertheless, precise channel estimation...
详细信息
The purpose of this work is to investigate the use of Natural Language Processing (NLP) techniques in the field of automated textbook summarisation. As a result of the exponential growth of digital content, there is a...
详细信息
Over the years, Cloud computing is becoming increasingly popular due to the continually changing technology. The primary goal of the cloud computing network is to offer consumers pay-per-use usage of on-demand process...
详细信息
Brain tumor detection is crucial for early diagnosis and treatment planning in the field of medical image analysis, particularly in neuroimaging. Deep learning techniques, including transfer learning, have shown great...
详细信息
Deep and machine learning models have become pivotal in medical image analysis, especially for diagnosing COVID-19 using X-rays and CT scans. While these models, including transfer learning-based approaches, have achi...
详细信息
Artificial Intelligence (AI) is transforming robotic cleaning systems to be more efficient, safe, and adapt in various environments, including public spaces and industrial facilities. The novelty of these systems is t...
详细信息
Data storage on cloud servers has become a common practice across businesses. Data security and accessibility in cloud environments are jeopardized when stored on unreliable cloud servers, making it necessary to conve...
详细信息
Efficient energy management is a cornerstone of advancing cognitive cities,where AI,IoT,and cloud computing seamlessly integrate to meet escalating global energy *** this context,the ability to forecast electricity co...
详细信息
Efficient energy management is a cornerstone of advancing cognitive cities,where AI,IoT,and cloud computing seamlessly integrate to meet escalating global energy *** this context,the ability to forecast electricity consumption with precision is vital,particularly in residential settings where usage patterns are highly variable and *** study presents an innovative approach to energy consumption forecasting using a bidirectional Long Short-Term Memory(LSTM)*** a dataset containing over twomillionmultivariate,time-series observations collected froma single household over nearly four years,ourmodel addresses the limitations of traditional time-series forecasting methods,which often struggle with temporal dependencies and non-linear *** bidirectional LSTM architecture processes data in both forward and backward directions,capturing past and future contexts at each time step,whereas existing unidirectional LSTMs consider only a single temporal *** design,combined with dropout regularization,leads to a 20.6%reduction in RMSE and an 18.8%improvement in MAE over conventional unidirectional LSTMs,demonstrating a substantial enhancement in prediction accuracy and *** to existing models—including SVM,Random Forest,MLP,ANN,and CNN—the proposed model achieves the lowest MAE of 0.0831 and RMSE of 0.2213 during testing,significantly outperforming these *** results highlight the model’s superior ability to navigate the complexities of energy usage patterns,reinforcing its potential application in AI-driven IoT and cloud-enabled energy management systems for cognitive *** integrating advanced machine learning techniqueswith IoT and cloud infrastructure,this research contributes to the development of intelligent,sustainable urban environments.
暂无评论