Load forecasting plays a crucial role in mitigating risks for utilities by predicting future usage of commodity markets transmission or supplied by the utility. To achieve this, various techniques such as price elasti...
详细信息
Load forecasting plays a crucial role in mitigating risks for utilities by predicting future usage of commodity markets transmission or supplied by the utility. To achieve this, various techniques such as price elastic demand, climate and consumer response, load analysis, and sustainable energy generation predictive modelling are used. As both supply and demand fluctuate, and weather and power prices can rise significantly during peak periods, accurate load forecasting becomes critical for utilities. By providing brief demand forecasts, load forecasting can assist in estimating load flows and making decisions that prevent overloading. Therefore, load forecasting is crucial in helping electric utilities make informed decisions related to power, load switching, voltage regulation, switching, and infrastructure development. Forecasting is a methodology used by electricity companies to forecast the amount of electricity or power production needed to maintain constant supply as well as load demand balance. It is required for the electrical industry to function properly. The smart grid is a new system that enables electricity providers and customers to communicate in real-time. The precise energy consumption sequence of the consumers is required to enhance the demand schedule. This is where predicting the future comes into play. Forecasting future power system load (electricity consumption) is a critical task in providing intelligence to the power grid. Accurate forecasting allows utility companies to allocate resources and assume system control in order to balance the same demand and availability for electricity. In this article, a study on load forecasting algorithms based on deep learning, machine learning, hybrid methods, bio-inspired techniques, and other techniques is carried out. Many other algorithms based on load forecasting are discussed in this study. Different methods of load forecasting were compared using three performance indices: RMSE (Root Mean Square Err
The medical domain faces unique challenges in Information Retrieval (IR) due to the complexity of medical language and terminology discrepancies between user queries and documents. While traditional Keyword-Based Meth...
详细信息
Accurately predicting the knee point cycle number,marking the onset of accelerated capacity degradation,is the first critical signal for managing lithium-ion battery life cycles in electric vehicles and stationary ene...
详细信息
Accurately predicting the knee point cycle number,marking the onset of accelerated capacity degradation,is the first critical signal for managing lithium-ion battery life cycles in electric vehicles and stationary energy storage ***,the inherent electrochemo-mechanical-thermal complexities of battery aging present significant challenges for physics-based models and machine-learning models,often leading to reduced predictive *** study developed a comprehensive dataset comprising 20 lithium nickel manganese cobalt oxide(NCM)/graphite cells(0.5-1 C) from our lab and 162 commercial lithium iron phosphate(LFP)/graphite cells(3-6 C) from the public database,with knee point observed between 100 and 1000 *** proposed a new strategy to extract novel features with strong physical context from early-cycle voltage curves,enabling precise knee point predictions across the chemistries without the need for extensive cycling *** model achieved a mean absolute percentage error(MAPE) of 7% for knee point prediction using five selected ***,the model yielded 8% MAPE with only one single feature across the initial 200 cycles,and 10% MAPE when applying five features across the initial 50 cycles,spanning different battery *** work highlights the potential of integrating multi-chemistry datasets with data-driven modeling to forecast aging patterns across diverse battery chemistries,advancing battery longevity and reliability.
The Internet of Vehicles (IoV) enhances road safety through real-time vehicle-to-vehicle (V2V) communication of traffic messages. However, V2V wireless connectivity poses security and privacy threats, as malicious adv...
详细信息
The skin acts as an important barrier between the body and the external environment, playing a vital role as an organ. The application of deep learning in the medical field to solve various health problems has generat...
详细信息
Improving website security to prevent malicious online activities is crucial,and CAPTCHA(Completely Automated Public Turing test to tell computers and Humans Apart)has emerged as a key strategy for distinguishing huma...
详细信息
Improving website security to prevent malicious online activities is crucial,and CAPTCHA(Completely Automated Public Turing test to tell computers and Humans Apart)has emerged as a key strategy for distinguishing human users from automated ***-based CAPTCHAs,designed to be easily decipherable by humans yet challenging for machines,are a common form of this ***,advancements in deep learning have facilitated the creation of models adept at recognizing these text-based CAPTCHAs with surprising *** our comprehensive investigation into CAPTCHA recognition,we have tailored the renowned UpDown image captioning model specifically for this *** approach innovatively combines an encoder to extract both global and local features,significantly boosting the model’s capability to identify complex details within CAPTCHA *** the decoding phase,we have adopted a refined attention mechanism,integrating enhanced visual attention with dual layers of Long Short-Term Memory(LSTM)networks to elevate CAPTCHA recognition *** rigorous testing across four varied datasets,including those from Weibo,BoC,Gregwar,and Captcha 0.3,demonstrates the versatility and effectiveness of our *** results not only highlight the efficiency of our approach but also offer profound insights into its applicability across different CAPTCHA types,contributing to a deeper understanding of CAPTCHA recognition technology.
Human action recognition is applicable in different domains. Previously proposed methods cannot appropriately consider the sequence of sub-actions. Herein, we propose a semantical action model based on the sequence of...
详细信息
Effective monitoring of the environment over a large area will require mobilization of a considerable amount of information. Otherwise, the use of traditional methods will prove to be costly and would take up so much ...
详细信息
Agriculture encompasses a way of life and a profession for the general population. Most global traditions and cultures revolve around agriculture. With the help of advanced farming, agriculture may become more profita...
详细信息
Searching the occurrences of specific code patterns (code search) is a common task in software engineering, and programming by example (PBE) techniques have been applied to ease customizing code patterns. However, pre...
详细信息
暂无评论