Predictive maintenance for power electronic converters has emerged as a critical area of
research and development. With the rapid advancements in deep-learning techniques, new …

Nowadays, the demand for power supply is increasing day by day due to industrialization,
population growth, and civilization. Therefore, it is crucial to meet this rising demand by …

With the commitment to climate, globally many countries started reducing brownfield energy
production and strongly opting towards green energy resources. However, the optimal …

Problem: The problem of the finalized exploration revolved around the inadequacy of current
traffic forecasting models. Despite decades of examination in many fields, existing …

The transition towards a sustainable energy system requires the integration of high-
penetration renewable energy sources (RESs) and the use of new energy management …

The burgeoning proliferation of integrated energy systems has fostered an unprecedented
degree of coupling among various energy streams, thereby elevating the necessity for …

In modern power systems, Inverter-Based Distributed Generators (IBDGs) are rapidly
increasing. Their aggregated effects alter the dynamic characteristics of the active …

Today, technology makes the management of soil health the key to sustainable, high-yield
agriculture. This article discusses a new approach using artificial intelligence and deep …

We present a new class of structured reinforcement learning policy-architectures, Implicit
Two-Tower (ITT) policies, where the actions are chosen based on the attention scores of …

The field of machine learning (ML) has achieved remarkable success over the past few
decades and has become an integral part of our daily lives, powering various applications …