Related papers: Sampling Model for Grid Material Inspection Based …
The quality of power grid equipment forms the material foundation for the safety of the large power grid. Ensuring the quality of equipment entering the grid is a core task in material management. Currently, the inspection of incoming…
With the increasing integration of smart meters in electrical grids worldwide, detecting energy theft has become a critical and ongoing challenge. Artificial intelligence (AI)-based models have demonstrated strong performance in identifying…
In the evolving field of maintenance and reliability engineering, the organization of equipment into hierarchical structures presents both a challenge and a necessity, directly impacting the operational integrity of industrial facilities.…
Demand forecasting in power sector has become an important part of modern demand management and response systems with the rise of smart metering enabled grids. Long Short-Term Memory (LSTM) shows promising results in predicting time series…
This study suggests a new strategy for improving congestion control by deploying Long Short-Term Memory (LSTM) networks. LSTMs are recurrent neural networks (RNN), that excel at capturing temporal relationships and patterns in data.…
Growing number of network devices and services have led to increasing demand for protective measures as hackers launch attacks to paralyze or steal information from victim systems. Intrusion Detection System (IDS) is one of the essential…
Predictive business process monitoring methods exploit logs of completed cases of a process in order to make predictions about running cases thereof. Existing methods in this space are tailor-made for specific prediction tasks. Moreover,…
Short Term Load Forecast (STLF) is necessary for effective scheduling, operation optimization trading, and decision-making for electricity consumers. Modern and efficient machine learning methods are recalled nowadays to manage complicated…
The automated wafer inspection and quality control is a complex and time-consuming task, which can speed up using neuromorphic memristive architectures, as a separate inspection device or integrating directly into sensors. This paper…
We study automated intrusion detection in an IT infrastructure, specifically the problem of identifying the start of an attack, the type of attack, and the sequence of actions an attacker takes, based on continuous measurements from the…
This research introduces a novel anomaly detection method designed to enhance the operational reliability of particle accelerators - complex machines that accelerate elementary particles to high speeds for various scientific applications.…
Consistency in product quality is of critical importance in manufacturing. However, achieving a target product quality typically involves balancing a large number of manufacturing attributes. Existing manufacturing practices for dealing…
While the use of the Internet of Things is becoming more and more popular, many security vulnerabilities are emerging with the large number of devices being introduced to the market. In this environment, IoT device identification methods…
Production Lines and Conveying Systems are the staple of modern manufacturing processes. Manufacturing efficiency is directly related to the efficiency of the means of production and conveying. Modelling in the industrial context has always…
Deep learning is a popular machine learning approach which has achieved a lot of progress in all traditional machine learning areas. Internet of thing (IoT) and Smart City deployments are generating large amounts of time-series sensor data…
The growing reliance on computer systems, particularly personal computers (PCs), necessitates heightened reliability to uphold user satisfaction. This research paper presents an in-depth analysis of extensive system telemetry data,…
Most electricity systems worldwide are deploying advanced metering infrastructures to collect relevant operational data. In particular, smart meters allow tracking electricity load consumption at a very disaggregated level and at high…
Accurate, non-invasive flow measurement is imperative for efficient water resource management and leak detection in distribution systems. Despite the advent of diverse external sensing technologies, a paucity of consolidated evidence exists…
As the adoption of Internet of Things (IoT) devices continues to rise in enterprise environments, the need for effective and efficient security measures becomes increasingly critical. This paper presents a cost-efficient platform to…
The ever-increasing demand to extract temporal correlations across sequential data and perform context-based learning in this era of big data has led to the development of long short-term memory (LSTM) networks. Furthermore, there is an…