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

Multiple Regression01:25

Multiple Regression

3.2K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
3.2K
Optimal Foraging00:48

Optimal Foraging

12.4K
How animals obtain and eat their food is called foraging behavior. Foraging can include searching for plants and hunting for prey and depends on the species and environment.
12.4K
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

100
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...
100
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

147
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...
147
Response Surface Methodology01:16

Response Surface Methodology

255
Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
255
Production Efficiency01:01

Production Efficiency

17.0K
Net production efficiency (NPE) is the efficiency at which organisms assimilate energy into biomass for the next trophic level. Due to low metabolic rates and less energy spent on thermoregulatory processes, the NPE of ectotherms (cold-blooded animals) is 10 times higher than endotherms (warm-blooded animals).
17.0K

You might also read

Related Articles

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

Sort by
Same journal

RETRACTION: Real-Time Modulation of Physical Training Intensity Based on Wavelet Recursive Fuzzy Neural Networks.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Multidimensional Heterogeneous Network Link Adaptation Based on Mobile Environment.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Framework to Segment and Evaluate Multiple Sclerosis Lesion in MRI Slices Using VGG-UNet.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Facial Emotion Recognition Using a Novel Fusion of Convolutional Neural Network and Local Binary Pattern in Crime Investigation.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Automatic Intelligent System Using Medical of Things for Multiple Sclerosis Detection.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Intangible Cultural Heritage Reproduction and Revitalization: Value Feedback, Practice, and Exploration Based on the IPA Model.

Computational intelligence and neuroscience·2026
See all related articles

Related Experiment Video

Updated: Sep 7, 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

Study on Sustainable Agricultural Structure Optimization Method Based on Multiobjective Optimization Algorithm.

Dingkang Duan1

  • 1Department of Economics, Belarusian State University, Minsk 220030, Belarus.

Computational Intelligence and Neuroscience
|June 23, 2022
PubMed
Summary
This summary is machine-generated.

Optimizing agricultural structure is key for sustainable development. This study develops a mathematical model to evaluate and guide agricultural industry structure optimization for better sustainability.

More Related Videos

Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology
06:24

Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology

Published on: December 15, 2017

10.2K
Optimization of the Epimedii Folium Mutton-Oil Processing Technology and Testing Its Effect on Zebrafish Embryonic Development
06:00

Optimization of the Epimedii Folium Mutton-Oil Processing Technology and Testing Its Effect on Zebrafish Embryonic Development

Published on: March 17, 2023

552

Related Experiment Videos

Last Updated: Sep 7, 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
Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology
06:24

Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology

Published on: December 15, 2017

10.2K
Optimization of the Epimedii Folium Mutton-Oil Processing Technology and Testing Its Effect on Zebrafish Embryonic Development
06:00

Optimization of the Epimedii Folium Mutton-Oil Processing Technology and Testing Its Effect on Zebrafish Embryonic Development

Published on: March 17, 2023

552

Area of Science:

  • Agricultural Science
  • Environmental Science
  • Operations Research

Background:

  • Sustainable agricultural development is crucial for human-nature harmony.
  • Current approaches lack robust scientific theoretical guidance for optimizing agricultural structures.
  • Adjusting agricultural structures is vital for enhancing sustainable development levels.

Purpose of the Study:

  • To address the lack of scientific guidance in agricultural sustainable development.
  • To study the theory and optimization of agricultural industry structure for sustainable development.
  • To develop a mathematical model for evaluating and optimizing agricultural sustainable development.

Main Methods:

  • Analysis of factors affecting agricultural sustainable development and key target indexes.
  • Application of multiobjective optimization theory.
  • Development and solution study of a mathematical model for evaluating agricultural sustainable development.

Main Results:

  • Identified key factors and target indexes for agricultural sustainable development.
  • Established a mathematical model for evaluating agricultural sustainable development.
  • Studied optimization methods for the multiobjective model.

Conclusions:

  • The developed mathematical model and solving method provide guidance for optimizing regional agricultural industrial structures.
  • The research enhances the quality of agricultural sustainable development.
  • This work contributes to the scientific theoretical foundation for agricultural sustainable development.