Results 61 to 70 of about 5,817,365 (365)

A Novel Multi-Objective Hybrid Evolutionary-Based Approach for Tuning Machine Learning Models in Short-Term Power Consumption Forecasting

AI
Accurately forecasting power consumption is crucial important for efficient energy management. Machine learning (ML) models are often employed for this purpose. However, tuning their hyperparameters is a complex and time-consuming task.
Aleksei Vakhnin, Ivan Ryzhikov, Harri Niska, Mikko Kolehmainen   +3 more
doaj   +1 more source

A large‐scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression‐free survival

Molecular Oncology, EarlyView.
There is an unmet need in metastatic breast cancer patients to monitor therapy response in real time. In this study, we show how a noninvasive and affordable strategy based on sequencing of plasma samples with longitudinal tracking of tumour fraction paired with a statistical model provides valuable information on treatment response in advance of the ...
Emma J. Beddowes, Mario Ortega Duran, Solon Karapanagiotis, Alistair Martin, Meiling Gao, Riccardo Masina, Ramona Woitek, James Tanner, Fleur Tippin, Justine Kane, Jonathan Lay, Anja Brouwer, Stephen‐John Sammut, Suet‐Feung Chin, Davina Gale, Dana W. Y. Tsui, Sarah‐Jane Dawson, Nitzan Rosenfeld, Maurizio Callari, Oscar M. Rueda, Carlos Caldas   +20 more
wiley   +1 more source

A Solution to the N-Queens Problem Using Biogeography-Based Optimization

International Journal of Interactive Multimedia and Artificial Intelligence, 2017
Biogeography-based Optimization (BBO) is a global optimization algorithm based on population, governed by mathematics of biogeography, and dealing with geographical distribution of biological organisms.
Ali Habiboghli, Tayebeh Jalali
doaj   +1 more source

Stability of evolutionary algorithms

Journal of Mathematical Analysis and Applications, 2008
AbstractWe prove under mild conditions the convergence of some evolutionary algorithm to the solution of the global optimization problem. In the proof, the Lyapunov function's techniques is applied to some semi-dynamical system generated by a Foias operator on the space of the probability measures defined on the set of admissible solutions.
openaire   +3 more sources

Time, the final frontier

Molecular Oncology, EarlyView.
This article advocates integrating temporal dynamics into cancer research. Rather than relying on static snapshots, researchers should increasingly consider adopting dynamic methods—such as live imaging, temporal omics, and liquid biopsies—to track how tumors evolve over time.
Gautier Follain, Michal Dibus, Omkar Joshi, Guillaume Jacquemet   +3 more
wiley   +1 more source

The Self-Organization of Interaction Networks for Nature-Inspired Optimization [PDF]

, 2008
Over the last decade, significant progress has been made in understanding complex biological systems, however there have been few attempts at incorporating this knowledge into nature inspired optimization algorithms.
Pham, Dr Q. Tuan, Sarker, Dr Ruhul A, Whitacre, Dr James M   +2 more
core  

Decomposition-Based Multi-Objective Evolutionary Algorithm Design Under Two Algorithm Frameworks

IEEE Access, 2020
The development of efficient and effective evolutionary multi-objective optimization (EMO) algorithms has been an active research topic in the evolutionary computation community. Over the years, many EMO algorithms have been proposed.
Lie Meng Pang, Hisao Ishibuchi, Ke Shang
doaj   +1 more source

Chemoresistome mapping in individual breast cancer patients unravels diversity in dynamic transcriptional adaptation

Molecular Oncology, EarlyView.
This study used longitudinal transcriptomics and gene‐pattern classification to uncover patient‐specific mechanisms of chemotherapy resistance in breast cancer. Findings reveal preexisting drug‐tolerant states in primary tumors and diverse gene rewiring patterns across patients, converging on a few dysregulated functional modules. Despite receiving the
Maya Dadiani, Gilgi Friedlander, Gili Perry, Nora Balint‐Lahat, Shlomit Gilad, Dana Morzaev‐Sulzbach, Anjana Shenoy, Noa Bossel Ben‐Moshe, Anya Pavlovsky, Rinat Bernstein‐Molho, Eytan Domany, Iris Barshack, Tamar Geiger, Bella Kaufman, Einav Nili Gal‐Yam   +14 more
wiley   +1 more source

Evolutionary Algorithm-Based Friction Feedforward Compensation for a Pneumatic Rotary Actuator Servo System

Applied Sciences, 2018
The friction interference in the pneumatic rotary actuator is the primary factor affecting the position accuracy of a pneumatic rotary actuator servo system.
Ke Li, Yeming Zhang, Shaoliang Wei, Hongwei Yue   +3 more
doaj   +1 more source

Particle Swarm Optimization with Independent Adaptive Parameter Adjustment

Jisuanji kexue yu tansuo, 2020
Aiming at the problems that traditional particle swarm optimization (PSO) algorithm is prone to fall into local optimum and depends on the value of parameters when solving complex optimization problems, an independent adaptive parameter adjustment ...
ZHANG Qiwen, WEI Yachen
doaj   +1 more source