Results 121 to 130 of about 87,787 (275)

Explainable artificial intelligence (XAI)‐powered design framework for lightweight strain‐hardening ultra‐high‐performance composites (SH‐UHPC)

Structural Concrete, EarlyView.
Abstract Lightweight strain‐hardening ultra‐high‐performance concrete composite (SH‐UHPC) is an outstanding alternative for engineering applications and infrastructure thanks to its outstanding strength, toughness, ductility, and low density. The integration of artificial intelligence (AI)‐based modeling strategies into engineering problems can ...
Metin Katlav, Kazim Turk
wiley   +1 more source

Local Search and the Evolution of World Models

Topics in Cognitive Science, EarlyView., 2023
Abstract An open question regarding how people develop their models of the world is how new candidates are generated for consideration out of infinitely many possibilities. We discuss the role that evolutionary mechanisms play in this process. Specifically, we argue that when it comes to developing a global world model, innovation is necessarily ...
Neil R. Bramley, Bonan Zhao, Tadeg Quillien, Christopher G. Lucas   +3 more
wiley   +1 more source

Choice Function-Based Hyper-Heuristics for Causal Discovery under Linear Structural Equation Models

Biomimetics
Causal discovery is central to human cognition, and learning directed acyclic graphs (DAGs) is its foundation. Recently, many nature-inspired meta-heuristic optimization algorithms have been proposed to serve as the basis for DAG learning.
Yinglong Dang, Xiaoguang Gao, Zidong Wang   +2 more
doaj   +1 more source

Meta-Heuristics Algorithms: A Survey

International Journal of Computer Applications, 2018
Nagham Ahmed, Ibrahim El-Henawy
openaire   +1 more source

Data privacy model using blockchain reinforcement federated learning approach for scalable internet of medical things

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Internet of Medical Things (IoMT) has typical advancements in the healthcare sector with rapid potential proof for decentralised communication systems that have been applied for collecting and monitoring COVID‐19 patient data. Machine Learning algorithms typically use the risk score of each patient based on risk factors, which could help ...
Chandramohan Dhasaratha, Mohammad Kamrul Hasan, Shayla Islam, Shailesh Khapre, Salwani Abdullah, Taher M. Ghazal, Ahmed Ibrahim Alzahrani, Nasser Alalwan, Nguyen Vo, Md Akhtaruzzaman   +9 more
wiley   +1 more source

Bio‐Inspired Optimisation Methods Applied to Low Carbon Power and Energy Problems: A Survey

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Bio‐inspired optimisation methods have been widely applied to complex real‐world problems, particularly in low‐carbon power and energy systems, where optimisation tasks often involve high‐dimensional, constrained and mixed‐integer characteristics.
Tianyu Hu, Shihao Zhao, Yuanjun Guo, Linxin Zhang, Zhile Yang   +4 more
wiley   +1 more source

A Universal Meta‐Heuristic Framework for Influence Maximisation in Hypergraphs

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Influence maximisation (IM) aims to select a small number of nodes that are able to maximise their influence in a network and covers a wide range of applications. Despite numerous attempts to provide effective solutions in simple networks, higher‐order interactions between entities in various real‐world systems are usually not taken into ...
Ming Xie, Chuang Liu, Yang Chen, Zi‐Ke Zhang, Xiaoyang Liu, Xiu‐Xiu Zhan   +5 more
wiley   +1 more source

Integrated transmission expansion planning incorporating fault current limiting devices and thyristor-controlled series compensation using meta-heuristic optimization techniques

Scientific Reports
Transmission expansion planning (TEP) is a vital process of ensuring power systems' reliable and efficient operation. The optimization of TEP is a complex challenge, necessitating the application of mathematical programming techniques and meta-heuristics.
Abdulaziz Almalaq, Khalid Alqunun, Rabeh Abbassi, Ziad M. Ali, Mohamed M. Refaat, Shady H. E. Abdel Aleem   +5 more
doaj   +1 more source

An Adaptive Genetic Algorithm for Solving N-Queens Problem

, 2017
In this paper a Metaheuristic approach for solving the N-Queens Problem is introduced to find the best possible solution in a reasonable amount of time. Genetic Algorithm is used with a novel fitness function as the Metaheuristic.
Nag, Sayan, Sarkar, Uddalok
core  

Solving TSP Using Various Meta-Heuristic Algorithms

International Journal of Recent Contributions from Engineering, Science & IT (iJES), 2013
Real world problems like Travelling Salesman Problem (TSP) belong to NP-hard optimization problems which are difficult to solve using classical mathematical methods. Therefore, many alternate solutions have been developed to find the optimal solution in shortest possible time.
openaire   +2 more sources