Review of metaheuristic optimization algorithms for power systems problems
Metaheuristic optimization algorithms are tools based on mathematical concepts that are
used to solve complicated optimization issues. These algorithms are intended to locate or …
used to solve complicated optimization issues. These algorithms are intended to locate or …
Nature inspired optimization algorithms: a comprehensive overview
Nature performs complex tasks in a simple yet efficient way. Natural processes may seem
straightforward from outside but are composed of several inherently complicated sub …
straightforward from outside but are composed of several inherently complicated sub …
From knowledge-based to big data analytic model: a novel IoT and machine learning based decision support system for predictive maintenance in Industry 4.0
Abstract The Internet of Things (IoT), Big Data and Machine Learning (ML) may represent
the foundations for implementing the concept of intelligent production, smart products …
the foundations for implementing the concept of intelligent production, smart products …
Soft sensors for state of charge, state of energy, and power loss in formula student electric vehicle
K Purohit, S Srivastava, V Nookala, V Joshi… - Applied System …, 2021 - mdpi.com
The proliferation of electric vehicle (EV) technology is an important step towards a more
sustainable future. In the current work, two-layer feed-forward artificial neural-network-based …
sustainable future. In the current work, two-layer feed-forward artificial neural-network-based …
[HTML][HTML] Distance to empty soft sensor for ford escape electric vehicle
Electric vehicle (EV) drivers require reliable distance to empty (DTE) indication to plan their
trips. In the current study, feed forward neural networks based soft sensors were designed to …
trips. In the current study, feed forward neural networks based soft sensors were designed to …
Lean manufacturing soft sensors for automotive industries
Lean and flexible manufacturing is a matter of necessity for the automotive industries today.
Rising consumer expectations, higher raw material and processing costs, and dynamic …
Rising consumer expectations, higher raw material and processing costs, and dynamic …
An improved marine predator algorithm based on epsilon dominance and Pareto archive for multi-objective optimization
Solving multi-objective optimization problems plays an important role in several
applications. Recently, the Marine Predator Algorithm (MPA) was introduced for solving …
applications. Recently, the Marine Predator Algorithm (MPA) was introduced for solving …
Machine learning-based predictive modeling and control of lean manufacturing in automotive parts manufacturing industry
The auto industry is critically dependent on lean and flexible manufacturing systems to
sustain in today's dynamic and price sensitive markets. In the current work, a machine …
sustain in today's dynamic and price sensitive markets. In the current work, a machine …
Using artificial intelligence to predict students' academic performance in blended learning
University electronic learning (e-learning) has witnessed phenomenal growth, especially in
2020, due to the COVID-19 pandemic. This type of education is significant because it …
2020, due to the COVID-19 pandemic. This type of education is significant because it …
Optimizing the machining conditions in turning hybrid aluminium nanocomposites adopting teaching–learning based optimization and MOORA technique
In this study, hybrid nanocomposites of aluminium (NHAMMCs) made from AA5052 are
fabricated via stir casting route by reinforcing 12 wt% Si3N4 and 0.5 wt% of graphene to …
fabricated via stir casting route by reinforcing 12 wt% Si3N4 and 0.5 wt% of graphene to …