Jove
Visualize
Contact Us
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 Concept Videos

Multimachine Stability01:25

Multimachine Stability

207
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
207
The Power Flow Problem and Solution01:26

The Power Flow Problem and Solution

277
Power flow problem analysis is fundamental for determining real and reactive power flows in network components, such as transmission lines, transformers, and loads. The power system's single-line diagram provides data on the bus, transmission line, and transformer. Each bus k in the system is characterized by four key variables: voltage magnitude Vk​, phase angle δk​, real power Pk​, and reactive power Qk​. Two of these four variables are inputs, while the...
277
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

142
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.
142
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

681
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
681
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

134
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
134
PD Controller: Design01:26

PD Controller: Design

298
In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
298

You might also read

Related Articles

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

Sort by
Same author

WAD-YOLO: A Lightweight Fall Detection Algorithm for Visual Sensor Systems Based on Wavelet Transform and Dynamic Convolution.

Sensors (Basel, Switzerland)·2026
Same author

The TDGL Module: A Fast Multi-Scale Vision Sensor Based on a Transformation Dilated Grouped Layer.

Sensors (Basel, Switzerland)·2026
Same author

Priority Control of Intelligent Connected Dedicated Bus Corridor Based on Deep Deterministic Policy Gradient.

Sensors (Basel, Switzerland)·2025
Same author

A Flexible Traffic Signal Coordinated Control Approach and System on Complicated Transportation Control Infrastructure.

Sensors (Basel, Switzerland)·2023
Same author

Investigation of multi-trait associations using pathway-based analysis of GWAS summary statistics.

BMC genomics·2019
Same author

Comparison of different functional prediction scores using a gene-based permutation model for identifying cancer driver genes.

BMC medical genomics·2019

Related Experiment Video

Updated: Jul 30, 2025

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

13.0K

Hierarchical Multi-Objective Optimization for Dedicated Bus Punctuality and Supply-Demand Balance Control.

Chunlin Shang1, Fenghua Zhu2, Yancai Xu2

  • 1College of Transportation, Ludong University, Yantai 264025, China.

Sensors (Basel, Switzerland)
|May 13, 2023
PubMed
Summary

This study introduces a new model to optimize bus speeds and schedules, significantly improving public transportation punctuality and balancing passenger demand. The research demonstrates a practical approach to reducing urban traffic congestion through enhanced bus services.

Keywords:
Lagrangian multiplier methoddedicated busdriving speed decision-makinghierarchical multi-objective optimizationintelligent transportation system

More Related Videos

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
14:55

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street

Published on: January 20, 2023

3.4K
Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation
11:41

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation

Published on: February 1, 2020

20.5K

Related Experiment Videos

Last Updated: Jul 30, 2025

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

13.0K
Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
14:55

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street

Published on: January 20, 2023

3.4K
Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation
11:41

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation

Published on: February 1, 2020

20.5K

Area of Science:

  • Urban Planning
  • Transportation Engineering
  • Operations Research

Background:

  • Public transportation is vital for reducing urban traffic congestion.
  • Improving bus punctuality and balancing supply with passenger demand are key challenges.
  • Current systems often struggle with efficiency and passenger satisfaction.

Purpose of the Study:

  • To develop a hierarchical multi-objective optimization model for bus operations.
  • To enhance bus punctuality and achieve supply-demand balance.
  • To optimize bus guidance speeds and operation schedules.

Main Methods:

  • Developed an intelligent decision-making method for bus driving speed using mathematical descriptions and the Lagrange multiplier method.
  • Proposed an optimization method for bus operation schedules, focusing on departure intervals and station timings.
  • Implemented and tested the model in Future Science City, Beijing.

Main Results:

  • Achieved a punctuality rate of 90.53% for the bus line.
  • Reduced the retention rate for platform passengers by 36.22%.
  • Decreased the intersection stop rate by 60.93%.

Conclusions:

  • The hierarchical multi-objective optimization model effectively improves bus punctuality and passenger experience.
  • The proposed methods demonstrate practical solutions for enhancing urban public transportation efficiency.
  • The findings validate the model's effectiveness in real-world urban environments.