Results 51 to 60 of about 53,710 (343)
Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data
Computers, 2022 Feature Selection in High Dimensional Space is a combinatory optimization problem with an NP-hard nature. Meta-heuristic searching with embedding information theory-based criteria in the fitness function for selecting the relevant features is used widely
Tara Othman Qadir Saraf +2 more
doaj +1 more source
ACO for continuous function optimization: a performance analysis [PDF]
, 2014 The performance of the meta-heuristic algorithms often depends on their parameter settings. Appropriate tuning of the underlying parameters can drastically improve the performance of a meta-heuristic. The Ant Colony Optimization (ACO), a population based
Abraham, Ajith +2 more
core
A Survey on Load Balancing Algorithms for VM Placement in Cloud Computing [PDF]
, 2017 The emergence of cloud computing based on virtualization technologies brings huge opportunities to host virtual resource at low cost without the need of owning any infrastructure.
Buyya, Rajkumar +2 more
core +2 more sources
In Situ Characterisation of Hydrogels via Dynamic Interface Printing
Advanced Science, EarlyView.ABSTRACT Hydrogels have become pivotal materials for tissue engineering, robotics, biomedical devices, and sensing applications due to their diverse material compositions and tunable mechanical properties. While significant effort has focused on developing novel manufacturing approaches such as extrusion bioprinting and light‐based fabrication methods,
Callum Vidler +2 more
wiley +1 more source
A Search-Based Test Data Generation Method for Concurrent Programs
International Journal of Computational Intelligence Systems, 2020 Concurrent programs are being widely adopted in development of multi-core and many-core processors. However, these types of programs present some features such as concurrency, communication and synchronization which make their testing more challenging ...
Seyed Mohsen Mirhosseini +1 more
doaj +1 more source
Time series predictive analysis based on hybridization of meta-heuristic algorithms [PDF]
, 2018 This paper presents a comparative study which involved five hybrid meta-heuristic methods to predict the weather five days in advance. The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial ...
Ernawan, Ferda +4 more
core
Training a Feed-forward Neural Network with Artificial Bee Colony Based Backpropagation Method
, 2012 Back-propagation algorithm is one of the most widely used and popular techniques to optimize the feed forward neural network training. Nature inspired meta-heuristic algorithms also provide derivative-free solution to optimize complex problem. Artificial
Das, Achintya +2 more
core +1 more source
Meta-heuristics and Artificial Intelligence [PDF]
, 2020 Meta-heuristics are generic search methods that are used to solve challenging combinatorial problems. We describe these methods and highlight their common features and differences by grouping them in two main kinds of approaches: Perturbative meta-heuristics that build new combinations by modifying existing combinations (such as, for example, genetic ...
Hao, Jin-Kao, Solnon, Christine
openaire +2 more sources
Advanced Science, EarlyView.Laterally spreading tumors (LSTs) are precancerous colorectal lesions characterized by a flat morphology. This study reveals a mechanochemical pathway through which a soft matrix microenvironment diminishes spatial constraints in intestinal adenomas. This process promotes deficiencies in tight junction proteins, mediated by the mechanoreceptor ADORA2B ...
Jiamin Zhong +21 more
wiley +1 more source
IEEE Access, 2022 This paper proposes a new meta-heuristic optimization algorithm, namely Mud Ring Algorithm (MRA) that mimics the mud ring feeding behaviour of bottlenose dolphins in the Atlantic coast of Florida.
Abeer S. Desuky +4 more
doaj +1 more source