Jove
Visualize
Contact Us

Related Concept Videos

Power01:08

Power

13.1K
The concept of work involves force and displacement; meanwhile, the work-energy theorem relates the net work done on a body to the difference in its kinetic energy, calculated between two points on its trajectory. While none of these quantities or relations involves time explicitly, we know that the time available to accomplish work is often just as important as the amount of work itself. For example, sprinters in a race may have achieved the same velocity at the finish, therefore,...
13.1K
Nuclear Power02:36

Nuclear Power

9.5K
Controlled nuclear fission reactions are used to generate electricity. Any nuclear reactor that produces power via the fission of uranium or plutonium by bombardment with neutrons has six components: nuclear fuel consisting of fissionable material, a nuclear moderator, a neutron source, control rods, reactor coolant, and a shield and containment system.
Nuclear Fuels
Nuclear fuel consists of a fissile isotope, such as uranium-235, which must be present in sufficient quantity to provide a...
9.5K
Power and Energy01:12

Power and Energy

2.1K
The power and energy delivered to an element are subjects of great significance in the field of electrical engineering. It is a well-known fact that a 100-watt light bulb emits more light than a 60-watt one. Therefore, power and energy calculations play a crucial role in the analysis of electrical circuits.
Power, defined as the time rate of expending or absorbing energy, is quantified in units called watts (W). The relation between power and energy is mathematically given as
2.1K
Average Power01:13

Average Power

1.1K
In practical electrical applications, the concept of time-varying instantaneous power is not frequently utilized. Instead, focus shifts to the more practical quantity known as average power. Average power is determined by integrating the instantaneous power over a specified time period and subsequently dividing it by that duration.
1.1K
Power Factor01:11

Power Factor

743
The power factor is defined as the ratio of average (or active) power to apparent power, as illustrated by the relation
743
Power System Distribution01:25

Power System Distribution

1.1K
Power system distribution involves delivering electrical energy from power plants to consumers through a network of transmission and distribution systems. The process begins at power plants, where energy from coal, gas, nuclear, water, and wind is converted into electrical energy. These plants use three-phase generators, typically rated between 50 to 1300 MVA, with terminal voltages ranging from a few kV to 20 kV, depending on the size and age of the units.
The transmission system is designed...
1.1K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Sensory-motor control with large language models via iterative policy refinement.

Scientific reports·2026
Same author

Human Expertise and Large Language Model Embeddings in the Content Validity Assessment of Personality Tests.

Educational and psychological measurement·2025
Same author

Global progress in competitive co-evolution: a systematic comparison of alternative methods.

Frontiers in robotics and AI·2025
Same author

Transformers deep learning models for missing data imputation: an application of the ReMasker model on a psychometric scale.

Frontiers in psychology·2025
Same author

Exploring the Potential of Variational Autoencoders for Modeling Nonlinear Relationships in Psychological Data.

Behavioral sciences (Basel, Switzerland)·2024
Same author

Interaction Rules Supporting Effective Flocking Behavior.

Artificial life·2024
Same journal

Thymidylate synthase inhibitory drugs induce p53-dependent pathways differently.

PloS one·2026
Same journal

Top-down and bottom-up attention for joint pattern classification and reconstruction.

PloS one·2026
Same journal

Short- and long-term scaling behavior of blood pressure and pulse arrival time during sleep in healthy controls and patients with obstructive sleep apnea.

PloS one·2026
Same journal

Double DQN-based secrecy energy efficiency and fairness performance in IRS-assisted NOMA systems with friendly jamming.

PloS one·2026
Same journal

10 recommendations for strengthening citizen science for improved societal and ecological outcomes: A co-produced analysis of challenges and opportunities in the 21st century.

PloS one·2026
Same journal

Paying in public: Peer effects, impression management, and willingness to pay on digital payment platforms.

PloS one·2026
See all related articles
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Feb 7, 2026

Adaptation of a Haptic Robot in a 3T fMRI
08:16

Adaptation of a Haptic Robot in a 3T fMRI

Published on: October 4, 2011

10.2K

Maximizing adaptive power in neuroevolution.

Paolo Pagliuca1, Nicola Milano1, Stefano Nolfi1

  • 1Institute of Cognitive Sciences and Technologies - National Research Council (CNR), Roma, Italia.

Plos One
|July 19, 2018
PubMed
Summary
This summary is machine-generated.

Two novel neuroevolutionary methods and Exponential Natural Evolutionary Strategy excel at the double-pole balancing problem, demonstrating robust, scalable, and fast solutions. Effective environmental adaptation and selective pressure regulation are key for successful artificial intelligence development.

More Related Videos

Visualizing Visual Adaptation
04:43

Visualizing Visual Adaptation

Published on: April 24, 2017

9.6K
The Power of Interstimulus Interval for the Assessment of Temporal Processing in Rodents
10:27

The Power of Interstimulus Interval for the Assessment of Temporal Processing in Rodents

Published on: April 19, 2019

7.4K

Related Experiment Videos

Last Updated: Feb 7, 2026

Adaptation of a Haptic Robot in a 3T fMRI
08:16

Adaptation of a Haptic Robot in a 3T fMRI

Published on: October 4, 2011

10.2K
Visualizing Visual Adaptation
04:43

Visualizing Visual Adaptation

Published on: April 24, 2017

9.6K
The Power of Interstimulus Interval for the Assessment of Temporal Processing in Rodents
10:27

The Power of Interstimulus Interval for the Assessment of Temporal Processing in Rodents

Published on: April 19, 2019

7.4K

Area of Science:

  • Artificial Intelligence
  • Computational Neuroscience
  • Evolutionary Computation

Background:

  • The double-pole balancing problem is a standard benchmark for evaluating artificial intelligence control strategies.
  • Neuroevolutionary methods are computational approaches inspired by biological evolution to develop artificial neural networks.
  • Assessing the robustness, speed, and scalability of these methods is crucial for advancing AI capabilities.

Purpose of the Study:

  • To systematically compare existing neuroevolutionary methods with two new approaches on the double-pole balancing task.
  • To evaluate methods based on solution robustness, discovery speed, and scalability to complex problems.
  • To identify optimal neuroevolutionary strategies and future research directions.

Main Methods:

  • Systematic comparison of leading neuroevolutionary algorithms.
  • Introduction and evaluation of two novel neuroevolutionary methods.
  • Testing on the double-pole balancing problem under varying environmental conditions.
  • Analysis of selective pressure and environmental variability effects.

Main Results:

  • The two novel methods and Exponential Natural Evolutionary Strategy significantly outperformed other approaches.
  • These top methods demonstrated superior robustness, speed, and scalability.
  • Regulating selective pressure and using variable environmental conditions proved critical for performance.

Conclusions:

  • Novel neuroevolutionary methods show significant promise for complex control tasks.
  • Environmental adaptation and selective pressure are vital factors in neuroevolution.
  • The findings guide the selection of effective methods and future research in AI.