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

Survival Tree01:19

Survival Tree

181
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
181
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

121
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...
121
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

6.5K
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
6.5K
Genetic Drift03:33

Genetic Drift

41.4K
Natural selection—probably the most well-known evolutionary mechanism—increases the prevalence of traits that enhance survival and reproduction. However, evolution does not merely propagate favorable traits, nor does it always benefit populations.
41.4K
Machines: Problem Solving II01:30

Machines: Problem Solving II

435
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
435
Machines: Problem Solving I01:22

Machines: Problem Solving I

463
A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
The toggle clamp system is a machine structure consisting of movable, pin-connected multi-force members that form a stabilized system to transmit forces. The...
463

You might also read

Related Articles

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

Sort by
Same journal

Supporting human-agent communication for explainable planning in spatial-temporal planning problems.

Neural computing & applications·2026
Same journal

Contrastive learning-based video quality assessment-jointed video vision transformer for video recognition.

Neural computing & applications·2026
Same journal

Sequential pattern transformer (SPT): a generative and interpretable framework for predicting disease trajectories.

Neural computing & applications·2026
Same journal

Balancing misclassification errors in image-based inference using problem domain semantics and a nested cascade architecture.

Neural computing & applications·2025
Same journal

Deep multi-objective reinforcement learning for utility-based infrastructural maintenance optimization.

Neural computing & applications·2025
Same journal

A fairness scale for real-time recidivism forecasts using a national database of convicted offenders.

Neural computing & applications·2025
See all related articles

Related Experiment Video

Updated: Oct 15, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.8K

Building fuzzy time series model from unsupervised learning technique and genetic algorithm.

Dinh Phamtoan1,2,3, Tai Vovan4

  • 1University of Science, Ho Chi Minh City, Vietnam.

Neural Computing & Applications
|October 25, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a novel fuzzy time series forecasting model. It optimizes clustering using genetic algorithms and effectively predicts future trends, demonstrating significant performance across diverse datasets.

Keywords:
Cluster analysisForecastFuzzy time seriesInterpolate

More Related Videos

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.5K
Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.7K

Related Experiment Videos

Last Updated: Oct 15, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.8K
Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.5K
Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.7K

Area of Science:

  • Data Science
  • Artificial Intelligence
  • Time Series Analysis

Background:

  • Accurate time series forecasting is crucial for various applications.
  • Existing fuzzy time series models often face challenges in optimal cluster determination and relationship establishment.
  • Effective interpolation and future prediction remain key research areas.

Purpose of the Study:

  • To propose a novel model for effective time series interpolation and future forecasting.
  • To integrate genetic algorithms for optimizing fuzzy clustering in time series analysis.
  • To develop a robust method for establishing fuzzy relationships and forecasting rules.

Main Methods:

  • Utilizing a genetic algorithm with an improved Davies and Bouldin index to optimize fuzzy clustering and determine the optimal number of clusters.
  • Developing a method to establish fuzzy relationships between time series elements and clusters.
  • Formulating forecasting rules based on the established fuzzy relationships.

Main Results:

  • The proposed model demonstrates significant performance improvements over existing methods across 3007 diverse time series.
  • MATLAB implementation confirms the model's effectiveness and practical applicability.
  • The model successfully forecasted COVID-19 victims in Vietnam, indicating broad applicability.

Conclusions:

  • The developed fuzzy time series model offers a powerful approach for interpolation and forecasting.
  • The integration of genetic algorithms enhances the optimization of fuzzy clustering for time series.
  • The model shows strong potential for real-world forecasting applications, including public health crises.