Results 71 to 80 of about 329,581 (308)
Quantum Genetic Algorithms for Computer Scientists
Computers, 2016 Genetic algorithms (GAs) are a class of evolutionary algorithms inspired by Darwinian natural selection. They are popular heuristic optimisation methods based on simulated genetic mechanisms, i.e., mutation, crossover, etc.
Rafael Lahoz-Beltra
doaj +1 more source
FEBS Open Bio, EarlyView.Unique biological samples, such as site‐specific mutant proteins, are available only in limited quantities. Here, we present a polarization‐resolved transient infrared spectroscopy setup with referencing to improve signal‐to‐noise tailored towards tracing small signals. We provide an overview of characterizing the excitation conditions for polarization‐
Clark Zahn, Karsten Heyne
wiley +1 more source
IEEE AccessThis study investigates the application of a Genetic Algorithm (GA) for optimizing scheduling in automated cube storage warehouses, focusing on enhancing logistics processing speed.
Won Yong Ha
doaj +1 more source
EXPRESS METHOD OF BARCODE GENERATION FROM FACIAL IMAGES [PDF]
Научно-технический вестник информационных технологий, механики и оптики, 2014 In the paper a method of generating of standard type linear barcodes from facial images is proposed. The method is based on use of the histogram of facial image brightness, averaging the histogram on a limited number of intervals, quantization of results
G. A. Kukharev +2 more
doaj
A Diversification Operator for Genetic Algorithms [PDF]
Conventional genetic algorithms suffer from a dependence on the initial generation used by the algorithm. In case the generation cosnsists of solutions which are not close enough to a global optimum but some of which are close to a relatively good local ...
Ghosh, Diptesh
core
Multiobjective gas turbine engine controller design using genetic algorithms
, 1996 This paper describes the use of multiobjective genetic algorithms (MOGAs) in the design of a multivariable control system for a gas turbine engine. The mechanisms employed to facilitate multiobjective search with the genetic algorithm are described with ...
Fleming, P., Chipperfield, Andrew
core +1 more source
FEBS Open Bio, EarlyView.In this study, we developed a deep learning method for mitotic figure counting in H&E‐stained whole‐slide images and evaluated its prognostic impact in 13 external validation cohorts from seven different cancer types. Patients with more mitotic figures per mm2 had significantly worse patient outcome in all the studied cancer types except colorectal ...
Joakim Kalsnes +32 more
wiley +1 more source
Higher-Order Quantum-Inspired Genetic Algorithms [PDF]
Annals of computer science and information systems, 2014 Robert Nowotniak, Jacek Kucharski
doaj +1 more source
APPLICATION OF THE DIRECTED MUTATION TO CELLULAR AUTOMATA GENERATION PROCESS [PDF]
Научно-технический вестник информационных технологий, механики и оптики, 2014 Cellular automata are widely used for the simulation of discrete systems. However, in most cases creation of controlling cellular automata is done manually, empirically or by exhaustive search. A number of papers describe methods for automatic generation
A. V. Tikhomirov, A. A. Shalyto
doaj
Genetic Algorithms: Genesis of Stock Evaluation [PDF]
The uncertainty of predicting stock prices emanates pre-eminent concerns around the functionality of the stock market. The possibility of utilising Genetic Algorithms to forecast the momentum of stock price has been previously explored by many ...
Rama Prasad Kanungo
core