Results 101 to 110 of about 116,877 (316)
Forecasting stock prices using Genetic Programming and Chance Discovery [PDF]
In recent years the computers have shown to be a powerful tool in financial forecasting. Many machine learning techniques have been utilized to predict movements in financial markets.
Edward P.K. Tsang +1 more
core
Modulation of Homer1 EVH1 domain internal dynamics by putative autism‐associated mutations
FEBS Letters, EarlyView.The putative autism‐associated M65I and S97L variants of the EVH1 domain of the postsynaptic scaffold protein Homer1 do not exhibit substantial changes in their overall structure or partner binding. Both of them, but especially the M65I variant, show altered internal dynamics relative to the wild‐type domain on the μs‐ms timescale, indicated by the ...
Fanni Farkas +6 more
wiley +1 more source
Automatic Generation of Cognitive Theories using Genetic Programming
, 2007 Cognitive neuroscience is the branch of neuroscience that studies the neural mechanisms underpinning cognition and develops theories explaining them. Within cognitive neuroscience, computational neuroscience focuses on modeling behavior, using theories ...
Frias-Martinez, E, Gobet, F
core +1 more source
Genetic Improvement of Programs [PDF]
2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, 2014 Genetic programming can optimise software, including: evolving test benchmarks, generating hyper-heuristics by searching meta-heuristics, generating communication protocols, composing telephony systems and web services, generating improved hashing and C++ heap managers, redundant programming and even automatic bug fixing.
openaire +1 more source
The ubiquitin‐proteasome system and autophagy as guardians of the cellular proteome
FEBS Letters, EarlyView.This Perspective covers the three principles governing the crosstalk between the ubiquitin‐proteasome system and autophagy in cellular proteostasis: (1) a shared ubiquitin code routing substrates via shuttle factors or autophagy receptors; (2) spatial compartmentalization into phase‐separated degradation hubs and organelle‐specific modules (exemplified
Ivan Dikic
wiley +1 more source
Predicting exchange rate volatility: genetic programming vs. GARCH and RiskMetrics [PDF]
This article investigates the use of genetic programming to forecast out-of-sample daily volatility in the foreign exchange market. Forecasting performance is evaluated relative to GARCH(1,1) and RiskMetrics models for two currencies, DEM and JPY ...
Christopher J. Neely, Paul A. Weller
core
Automatic Heuristic Generation with Scatter Programming to Solve the Hybrid Flow Shop Problem
Advances in Mechanical Engineering, 2015 The hybrid flow shop (HFS) problem is solved in this study through composite dispatching rules (CDRs) generated automatically. CDR is a simple approach to solve the HFS problem rapidly and easily.
Wen Shi, Xueyan Song, Jizhou Sun
doaj +1 more source
Genetic Programming and Emergence [PDF]
Genetic Programming and Evolvable Machines, 2013 Emergence and its accompanying phenomena are a widespread process in nature. Despite its prominence, there is no agreement in the sciences about the concept and how to define or measure emergence. One of the most contentious issues discussed is that of top-down (or downward) causation as a defining characteristic of systems with emergence.
openaire +1 more source
From mice to humans—divergent strategies for intestinal homeostasis and regeneration
FEBS Letters, EarlyView.Recent advances such as organoid genome editing, xenotransplantation, imaging, and whole‐genome sequencing have enabled direct studies of human intestinal stem cells (ISCs). These studies reveal species‐specific features, including slower ISC proliferation, distinct injury responses, slower somatic mutation accumulation in humans, and an inverse ...
Keiko Ishikawa +2 more
wiley +1 more source
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2020 Una-May O'Reilly, Erik Hemberg
openaire +2 more sources