Results 41 to 50 of about 2,832,903 (299)

A Genetic Programming-Driven Data Fitting Method

IEEE Access, 2020
Data fitting is the process of constructing a curve, or a set of mathematical functions, that has the best fit to a series of data points. Different with constructing a fitting model from same type of function, such as the polynomial model, we notice ...
Hao Chen, Zi Yuan Guo, Hong Bai Duan, Duo Ban   +3 more
doaj   +1 more source

Solid Pseudopapillary Neoplasm of the Pancreas in Children and Adolescents: Expert Recommendations

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Solid pseudopapillary neoplasm of the pancreas (SPN) is a rare low‐grade malignant exocrine pancreatic tumor, mostly discovered during the second decade of life in females, with a very good prognosis, provided microscopically complete surgical excision is achieved.
Sabine Irtan, Michael Abele, Calogero Virgone, Michaela Kuhlen, Ricardo Lopez‐Almarez, Tal Ben‐Ami, Ewa Bien, Maja Cesen, Malgorzata A. Krawczyk, Andrea Ferrari, Gianni Bisogno, Yves Reguerre, Dominik T. Schneider, Louise Galmiche, Jorg Fuchs, Sarah Braungart, Bilgehan Yalcin, Ines B. Brecht, Daniel Orbach   +18 more
wiley   +1 more source

Genetic Programming with Guaranteed Constraints [PDF]

, 2002
Genetic programming is a powerful technique for automatically generating program code from a description of the desired functionality. However it is frequently distrusted by users because the programs are generated with reference to a training set, and ...
Johnson, Colin G.
core  

Imperative Genetic Programming

Symmetry
Genetic programming (GP) has a long-standing tradition in the evolution of computer programs, predominantly utilizing tree and linear paradigms, each with distinct advantages and limitations. Despite the rapid growth of the GP field, there have been disproportionately few attempts to evolve ’real’ Turing-like imperative programs (as contrasted with ...
Iztok Fajfar, Ziga Rojec, Árpád Bürmen, Matevz Kunaver, Tadej Tuma, Saso Tomazic, Janez Puhan   +6 more
openaire   +3 more sources

A genetic programming ecosystem [PDF]

Proceedings 15th International Parallel and Distributed Processing Symposium. IPDPS 2001, 2005
Algorithms are needed in every aspect of parallel computing. Genetic Programming is an evolutionary technique for automating the design of algorithms through iterative steps of mutation and crossover operations on an initial population of randomly generated computer programs.
Judith Ellen Devaney, John G. Hagedorn, Olivier Nicolas, Gagan Garg, Aurelien Samson, Martial Michel   +5 more
openaire   +1 more source

A comparison of machine learning techniques for survival prediction in breast cancer

BioData Mining, 2011
Background The ability to accurately classify cancer patients into risk classes, i.e. to predict the outcome of the pathology on an individual basis, is a key ingredient in making therapeutic decisions.
Vanneschi Leonardo, Farinaccio Antonella, Mauri Giancarlo, Antoniotti Mauro, Provero Paolo, Giacobini Mario   +5 more
doaj   +1 more source

Hydropower Unit Commitment Using a Genetic Algorithm with Dynamic Programming

Energies, 2023
This study presents a genetic algorithm integrated with dynamic programming to address the challenges of the hydropower unit commitment problem, which is a nonlinear, nonconvex, and discrete optimization, involving the hourly scheduling of generators in ...
Shuangquan Liu, Pengcheng Wang, Zifan Xu, Zhipeng Feng, Congtong Zhang, Jinwen Wang, Cheng Chen   +6 more
doaj   +1 more source

Provider and Parent Perspectives on Prioritizing the “Asking and Monitoring” Pediatric Cancer Psychosocial Standards of Care

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background The Standards for Psychosocial Care for Children with Cancer and Their Families (“Standards”) are evidence‐based guidelines for psychosocial care in pediatric oncology. Care related to the three “Asking and Monitoring” Standards—Assessment of Psychosocial Needs, Assessment of Financial Needs, and Monitoring Neurocognitive Problems ...
Julia B. Tager, Natalie Koskela‐Staples, Emily M. Pariseau, Michele Scialla, Kimberly Buff, Lori Wiener, Victoria Sardi Brown, Anne E. Kazak, Kimberly S. Canter   +8 more
wiley   +1 more source

Grammar-based genetic programming : a survey [PDF]

, 2010
Grammar formalisms are one of the key representation structures in Computer Science. So it is not surprising that they have also become important as a method for formalizing constraints in Genetic Programming (GP).
Whigham, P. A. (Peter A.), O\u27Neill, Michael, O'Neill, Michael, McKay, Bob (Bob I.), Nguyen, Xuan Hoai, Shan, Yin   +5 more
core   +1 more source

Analysis and prediction of carbon emission factors based on genetic programming

Results in Engineering
In recent years, frequent extreme weather events such as storms and floods globally have made carbon emission reduction a critical issue for addressing environmental challenges through sustainable green pathways.
Wenchao Pan, Tsungxian Lin, Tzuhsiung Lin, Qilin Du, Lili Wu, Qinyi Lin   +5 more
doaj   +1 more source