Results 71 to 80 of about 174,883 (339)
Improved Evolvability in Genetic Programming with Polyandry
South African Computer Journal, 2013 This paper proposes Polyandry, a new nature-inspired modification to canonical Genetic Programming (GP). Polyandry aims to improve evolvability in GP. Evolvability is a critically important GP trait, the maintenance of which determines the arrival of the
Anisa Waganda Ragalo
doaj
Software Effort Estimation Using Multi Expression Programming [PDF]
Al-Rafidain Journal of Computer Sciences and Mathematics, 2014 The process of finding a function that can estimate the effort of software systems is considered to be the most important and most complex process facing systems developers in the field of software engineering.
Najla Al-Saati, Taghreed Alreffaee
doaj +1 more source
Solving classification problems using Traceless Genetic Programming [PDF]
World Computer Congress, The Symposium on Professional Practice in
AI, 26-29 August, Toulouse, France, edited by E. Mercier-Laurent, J.
Debenham, pp. 403-412, 2004, 2021 Traceless Genetic Programming (TGP) is a new Genetic Programming (GP) that may be used for solving difficult real-world problems. The main difference between TGP and other GP techniques is that TGP does not explicitly store the evolved computer programs.
arxiv
Molecular Oncology, EarlyView.Urine is a rich source of biomarkers for cancer detection. Tumor‐derived material is released into the bloodstream and transported to the urine. Urine can easily be collected from individuals, allowing non‐invasive cancer detection. This review discusses the rationale behind urine‐based cancer detection and its potential for cancer diagnostics ...
Birgit M. M. Wever +1 more
wiley +1 more source
Accurate High Performance Concrete Prediction with an Alignment-Based Genetic Programming System
International Journal of Concrete Structures and Materials, 2018 In 2013, our research group published a contribution in which a new version of genetic programming, called Geometric Semantic Genetic Programming (GSGP), was fostered as an appropriate computational intelligence method for predicting the strength of high-
Leonardo Vanneschi +3 more
doaj +1 more source
Imperative Genetic Programming
SymmetryGenetic 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 +6 more
openaire +3 more sources
Surfaceome: a new era in the discovery of immune evasion mechanisms of circulating tumor cells
Molecular Oncology, EarlyView.In the era of immunotherapies, many patients either do not respond or eventually develop resistance. We propose to pave the way for proteomic analysis of surface‐expressed proteins called surfaceome, of circulating tumor cells. This approach seeks to identify immune evasion mechanisms and discover potential therapeutic targets. Circulating tumor cells (
Doryan Masmoudi +3 more
wiley +1 more source
Genetic Programming for Object Detection: A Two-Phase Approach with an Improved Fitness Function
ELCVIA Electronic Letters on Computer Vision and Image Analysis, 2007 This paper describes two innovations that improve the efficiency and effectiveness of a genetic programming approach to object detection problems. The approach uses genetic programming to construct object detection programs that are applied, in a moving ...
Mengjie Zhang, Urvesh Bhowan, Bunna Ny
doaj +1 more source
Evolving Matrix-Factorization-Based Collaborative Filtering Using Genetic Programming
Applied Sciences, 2020 Recommender systems aim to estimate the judgment or opinion that a user might offer to an item. Matrix-factorization-based collaborative filtering typifies both users and items as vectors of factors inferred from item rating patterns.
Raúl Lara-Cabrera +3 more
doaj +1 more source