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Related Concept Videos

Health Information Technology and Healthcare Information System01:30

Health Information Technology and Healthcare Information System

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Health Information Technology (HIT)
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

40
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...
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Nursing Clinical Information System01:27

Nursing Clinical Information System

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Nursing Clinical Information System (NCIS)
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
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Multimachine Stability01:25

Multimachine Stability

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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:
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Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

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The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
171
Design Example: Alignment of a Road Line Using GIS01:17

Design Example: Alignment of a Road Line Using GIS

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The alignment of a road line using Geographic Information Systems (GIS) is a critical process in civil engineering, combining advanced technology with practical decision-making. This methodology begins with the collection of geospatial data, including information on land cover, geomorphology, drainage patterns, slope, and contour details. Such data is typically acquired through satellite imagery and GIS tools, offering a comprehensive understanding of the terrain.Once the data is gathered, it...
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Related Experiment Video

Updated: Jun 5, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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Design of information management model based on multiobjective optimization algorithm in intelligent electric

Junhui Hu1, Hongxiang Cai2, Shiyong Zhang2

  • 1State Grid Ningbo Electric Power Supply Company, Ningbo, Zhejiang, China.

Peerj. Computer Science
|December 13, 2024
PubMed
Summary

This study optimizes electric power systems by integrating fuel cost, network loss, and voltage quality using a novel differential evolutionary algorithm. The enhanced approach improves resource allocation and information management in intelligent power grids.

Keywords:
Adaptive variabilityConstraintsInformation management modelMulti-objective optimizationOperator dynamic cross-factorsPower financial system

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Area of Science:

  • Electrical Engineering
  • Operations Research
  • Computer Science

Background:

  • Intelligent electric power systems face inefficiencies in information management, leading to resource depletion.
  • Optimizing power systems requires balancing economic, environmental, and societal objectives.

Purpose of the Study:

  • To develop a multiobjective optimization algorithm for integrated design and operational scheduling of electric power systems.
  • To optimize fuel cost, active network loss, and voltage quality simultaneously.

Main Methods:

  • A mathematical model was developed incorporating fuel cost, network loss, and voltage quality objectives with constraints.
  • An enhanced differential evolutionary algorithm (DE) was introduced with adaptive variation and dynamic crossover factors.
  • Adaptive grid and cyclic crowding degree methods were used to maintain population diversity and Pareto front distribution.

Main Results:

  • The enhanced DE algorithm demonstrated robust convergence and distribution performance on standard test functions (ZDT1, ZDT2, ZDT3, ZDT4).
  • Convergence indices on ZDT1 and ZDT2 were 0.000938 and 0.0034, respectively.
  • Distribution indices on ZDT1, ZDT2, ZDT3, and ZDT4 were 0.0018, 0.0026, 0.0027, and 0.0009, respectively.

Conclusions:

  • The proposed multiobjective optimization approach effectively enhances electric power financial information management.
  • The intelligent handling of power system information leads to improved material and financial resource allocation.