Results 11 to 20 of about 39,370 (118)

Fitness Landscape Analysis of Weight-Elimination Neural Networks

Neural Processing Letters, 2017
Neural network architectures can be regularised by adding a penalty term to the objective function, thus minimising network complexity in addition to the error. However, adding a term to the objective function inevitably changes the surface of the objective function.
Anna S. Bosman, Andries P. Engelbrecht, Mardé Helbig   +2 more
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Complex network analysis of fitness landscapes

, 2016
The concept of fitness landscapes originated from evolutionary biology and is relevant for numerous disciplines. In metaheuristics for combinatorial optimization, fitness landscapes are frequently used to study the structure of problems. A novel approach is to analyze fitness landscapes by local optima networks'' (LONs).
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Structural Analysis of Benchmarking Fitness Landscapes

Scientific Journal of Riga Technical University. Computer Sciences, 2010
Galina Merkuryeva, Vitalijs Bolshakovs
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Visual analysis of fitness landscapes in architectural design optimization

The Visual Computer
AbstractIn architectural design optimization, fitness landscapes are used to visualize design space parameters in relation to one or more objective functions for which they are being optimized. In our design study with domain experts, we developed a visual analytics framework for exploring and analyzing fitness landscapes spanning data, projection, and
Moataz Abdelaal, Marcel Galuschka, Max Zorn, Fabian Kannenberg, Achim Menges, Thomas Wortmann, Daniel Weiskopf, Kuno Kurzhals   +7 more
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Fitness Landscape Analysis of Product Unit Neural Networks

Algorithms
A fitness landscape analysis of the loss surfaces produced by product unit neural networks is performed in order to gain a better understanding of the impact of product units on the characteristics of the loss surfaces. The loss surface characteristics of product unit neural networks are then compared to the characteristics of loss surfaces produced by
Andries P. Engelbrecht, Robert Gouldie
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Fitness Landscape Analysis on Binary Dynamic Optimization Problems

Procedia Computer Science, 2022
Bernhard Werth, Andreas Beham, Johannes Karder, Stefan Wagner 0002, Michael Affenzeller   +4 more
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A Q-Learning-Enhanced Cuckoo Catfish Optimizer (CCO-RL): A Comparative Study of Nine Metaheuristics Applied to CEC2017, CEC2022 and Engineering Design Problems. [PDF]

Biomimetics (Basel)
Tawil AA, Alshahrani A, Alqudah BI, Fathi H.   +3 more
europepmc   +1 more source

Descent from a common ancestor restricts exploration of protein sequence space. [PDF]

Proc Natl Acad Sci U S A
Isakova LH, Streltsova E, Bochkareva OO, Vlasov PK, Kondrashov FA.   +4 more
europepmc   +1 more source

D-LIM: A neural network for interpretable gene-gene interactions. [PDF]

PLoS Comput Biol
Wang S, Allauzen A, Nghe P, Opuu V.
europepmc   +1 more source

Fitness landscape-based analysis of nature-inspired algorithms

As the number of nature-inspired algorithms increases so does the need to characterise these algorithms. A rigorous process to characterise algorithms helps practitioners decide which algorithms may offer a good fit for their given problem. One approach is to relate the characteristics of a problem's associated fitness landscape with the performance of
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