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Related Concept Videos

Heuristics01:21

Heuristics

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Heuristics are problem-solving strategies that use mental shortcuts to simplify decision-making. Unlike algorithms, which must be followed precisely to achieve a correct result, heuristics offer a general problem-solving framework. They save time and energy but can sometimes lead to less rational decisions.
People often rely on heuristics when faced with an overload of information, limited time, low importance of the decision, limited information, or when a heuristic readily comes to mind. For...
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Statically Indeterminate Problem Solving01:16

Statically Indeterminate Problem Solving

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Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...
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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.
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Normal and Tangetial Components: Problem Solving01:24

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Consider a man with a mass of 70 kg seated in a chair connected to a pin support through a member BC. If the man maintains an upright position, the task is to determine the horizontal and vertical reactions of the chair on the man when the member makes a 45° angle with the horizontal. At this moment, the man has a speed of 5 m/s, increasing at a rate of 1 m/s².
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Moment of a Couple: Problem Solving01:30

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The moment of couple is an essential concept in physics and engineering, used to calculate the rotational force, or torque, that is created when a couple —two equal and opposite forces—acts on an object.
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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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A novel Human Conception Optimizer for solving optimization problems.

Debasis Acharya1, Dushmanta Kumar Das2

  • 1Department of Electrical and Electronics Engineering, National Institute of Technology Nagaland, Dimapur, 797103, India.

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|December 14, 2022
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Summary
This summary is machine-generated.

A new metaheuristic algorithm, the Human Conception Optimizer (HCO), models human conception to solve complex optimization problems. This novel computational technique shows significant improvements in engineering applications, outperforming existing methods.

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Area of Science:

  • Computational Intelligence
  • Optimization Algorithms
  • Bio-inspired Computing

Background:

  • Complex optimization problems are prevalent across diverse scientific and engineering fields.
  • Existing metaheuristic algorithms often require further refinement for enhanced performance.
  • Biological processes offer novel inspiration for developing advanced computational methods.

Purpose of the Study:

  • To introduce the Human Conception Optimizer (HCO), a novel metaheuristic algorithm inspired by human conception.
  • To mathematically model the sperm's search strategy for egg fertilization.
  • To evaluate the HCO algorithm's effectiveness in solving optimization problems.

Main Methods:

  • Mathematical modeling of biological principles from human conception (e.g., sperm selection, guidance, motility, hyperactivation).
  • Implementation of the HCO algorithm to find optimal solutions.
  • Benchmarking against IEEE CEC-2005 and IEEE CEC-2020 test functions.
  • Comparative analysis with existing optimization algorithms.
  • Validation on real-world engineering problems: over-current relay coordination and PID controller design for mechanical ventilators.

Main Results:

  • The HCO algorithm demonstrated strong performance on benchmark test functions.
  • Significant improvements were observed in real-world engineering applications.
  • A 50%-60% reduction in total relay operating times for an IEEE 8-bus distribution system.
  • Enhanced response and settling times for a mechanical ventilator's PID controller.

Conclusions:

  • The Human Conception Optimizer (HCO) is a viable and effective metaheuristic algorithm for complex optimization tasks.
  • HCO offers a promising bio-inspired approach with practical advantages in engineering problem-solving.
  • The algorithm's performance suggests potential for broader applications in computational intelligence.