Jove
Visualize
Contact Us

Related Concept Videos

Methods of Medium Optimization01:28

Methods of Medium Optimization

70
Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...
70
Application of Differentiation to Business01:29

Application of Differentiation to Business

343
Calculus offers essential techniques for businesses seeking to optimize pricing strategies and revenue. In this case, a bakery wants to determine the ideal price and daily sales volume to maximize revenue. By modeling how changes in price affect demand and revenue, the bakery can apply calculus to make data-driven decisions.The demand function relates the price per cupcake to the number of cupcakes sold and captures how lower prices increase sales. Based on market data, the demand function can...
343
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

777
The maximum power flow for lossy transmission lines is derived using ABCD parameters in phasor form. These parameters create a matrix relationship between the sending-end and receiving-end voltages and currents, allowing the determination of the receiving-end current. This relationship facilitates calculating the complex power delivered to the receiving end, from which real and reactive power components are derived.
777
Optimization Problems01:26

Optimization Problems

220
Optimization problems often involve identifying maximum or minimum values under specific constraints. A well-known example is determining the longest horizontal pipe that can be moved around a right-angled corner, where a 3-meter-wide hallway meets a 2-meter-wide hallway. This scenario, common in architectural design and industrial transport, can be understood conceptually through geometric and trigonometric reasoning.To visualize the problem, consider the pipe as a straight line that touches...
220
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

438
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
438
Load-frequency control01:28

Load-frequency control

894
Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...
894

You might also read

Related Articles

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

Sort by
Same author

An Indoor Location-Based Augmented Reality Framework.

Sensors (Basel, Switzerland)·2023
Same author

Deep Learning Anomaly Classification Using Multi-Attention Residual Blocks for Industrial Control Systems.

Sensors (Basel, Switzerland)·2022
Same author

Fingerprint Feature Extraction for Indoor Localization.

Sensors (Basel, Switzerland)·2021
Same author

Time Series Multiple Channel Convolutional Neural Network with Attention-Based Long Short-Term Memory for Predicting Bearing Remaining Useful Life.

Sensors (Basel, Switzerland)·2020
Same author

Evolutionary Beamforming Optimization for Radio Frequency Charging in Wireless Rechargeable Sensor Networks.

Sensors (Basel, Switzerland)·2017
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: May 3, 2026

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

12.6K

Pricing resources in LTE networks through multiobjective optimization.

Yung-Liang Lai1, Jehn-Ruey Jiang2

  • 1Department of Computer Science and Information Engineering, Taoyuan Innovation Institute of Technology, Taoyuan, Jhongli 32001, Taiwan.

Thescientificworldjournal
|February 15, 2014
PubMed
Summary
This summary is machine-generated.

This study introduces a method for optimizing resource pricing in Long-Term Evolution (LTE) networks to balance operator profit and user satisfaction, aiming to reduce customer churn.

Related Experiment Videos

Last Updated: May 3, 2026

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

12.6K

Area of Science:

  • Telecommunications Engineering
  • Network Optimization
  • Operations Research

Background:

  • Long-Term Evolution (LTE) networks provide versatile mobile services requiring differential Quality of Service (QoS) to enhance user satisfaction.
  • LTE operators face a challenge in pricing resources to maximize profits while maintaining user satisfaction and preventing subscriber churn.

Purpose of the Study:

  • To address the pricing resources with profits and satisfaction optimization (PRPSO) problem in LTE networks.
  • To simultaneously optimize operator profit and subscriber satisfaction.

Main Methods:

  • The PRPSO problem is modeled as a nonlinear multiobjective optimization problem.
  • The study proposes a solution based on the Non-dominated Sorting Genetic Algorithm II (NSGA-II) framework.
  • Simulations are used to evaluate the performance of the proposed solution.

Main Results:

  • The proposed NSGA-II based approach effectively balances operator profit maximization and user satisfaction.
  • The method provides a framework for dynamic resource pricing strategies in LTE networks.
  • Evaluations demonstrate the feasibility and effectiveness of the optimization approach.

Conclusions:

  • Optimizing resource pricing in LTE networks is crucial for achieving both economic viability and user retention.
  • The NSGA-II framework offers a robust method for solving complex multiobjective optimization problems in telecommunications.
  • The PRPSO model provides valuable insights for operators seeking to improve service offerings and customer loyalty.