Imagen de Portada

Advanced Artificial Intelligence Strategy for Optimizing Urban Rail Network Design using Nature-Inspired Algorithms

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Kumar, Hariram Sampath, Singh, Archana, Ojha, Manish Kumar
Formato:	Preprint
Publicado:	2024
Materias:	Neural and Evolutionary Computing Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Artificial Intelligence Based Navigation in Quasi Structured Environment
por: Kumar, Hariram Sampath, et al.
Publicado: (2024)

SHS: Scorpion Hunting Strategy Swarm Algorithm
por: Singh, Abhilash, et al.
Publicado: (2024)

Enhancing Decision-Making in Optimization through LLM-Assisted Inference: A Neural Networks Perspective
por: Singh, Gaurav, et al.
Publicado: (2024)

An Introductory Review of Spiking Neural Network and Artificial Neural Network: From Biological Intelligence to Artificial Intelligence
por: Zheng, Shengjie, et al.
Publicado: (2022)

Towards Self-constructive Artificial Intelligence: Algorithmic basis (Part I)
por: Corbacho, Fernando J.
Publicado: (2019)

GEGO: A Hybrid Golden Eagle and Genetic Optimization Algorithm for Efficient Hyperparameter Tuning in Resource-Constrained Environments
por: Nazarians, Amaras, et al.
Publicado: (2026)

Applications of Nature-Inspired Metaheuristic Algorithms for Tackling Optimization Problems Across Disciplines
por: Cui, Elvis Han, et al.
Publicado: (2023)

Towards Robust and Accurate Myoelectric Controller Design based on Multi-objective Optimization using Evolutionary Computation
por: Shaikh, Ahmed Aqeel, et al.
Publicado: (2022)

DECN: Evolution Inspired Deep Convolution Network for Black-box Optimization
por: Wu, Kai, et al.
Publicado: (2023)

Modularity is the Bedrock of Natural and Artificial Intelligence
por: Salatiello, Alessandro
Publicado: (2026)

Evolutionary Computation for the Design and Enrichment of General-Purpose Artificial Intelligence Systems: Survey and Prospects
por: Poyatos, Javier, et al.
Publicado: (2024)

Quantum Inspired Chaotic Salp Swarm Optimization for Dynamic Optimization
por: Pathak, Sanjai, et al.
Publicado: (2024)

Image Classification Method using Dynamic Quantum Inspired Genetic Algorithm
por: Singh, Akhilesh Kumar, et al.
Publicado: (2025)

Training neural networks without backpropagation using particles
por: Kumar, Deepak
Publicado: (2024)

Strategies for Resource Allocation of Two Competing Companies using Genetic Algorithm
por: Cheung, Wing Keung, et al.
Publicado: (2025)

SAIS: A Novel Bio-Inspired Artificial Immune System Based on Symbiotic Paradigm
por: Song, Junhao, et al.
Publicado: (2024)

Residual Learning Inspired Crossover Operator and Strategy Enhancements for Evolutionary Multitasking
por: Wang, Ruilin, et al.
Publicado: (2025)

Particle Swarm Optimization based on Novelty Search
por: Misra, Mr. Rajesh, et al.
Publicado: (2022)

Reinforcement learning Based Automated Design of Differential Evolution Algorithm for Black-box Optimization
por: Yang, Xu, et al.
Publicado: (2025)

A Tutorial on the Design, Experimentation and Application of Metaheuristic Algorithms to Real-World Optimization Problems
por: Osaba, Eneko, et al.
Publicado: (2024)

Spiking Neural Networks: The Future of Brain-Inspired Computing
por: Aribe Jr, Sales G.
Publicado: (2025)

A Genetic Algorithm for Multi-Capacity Fixed-Charge Flow Network Design
por: Eardley, Caleb, et al.
Publicado: (2024)

SeaEvo: Advancing Algorithm Discovery with Strategy Space Evolution
por: Luo, Sichun, et al.
Publicado: (2026)

Life-inspired Interoceptive Artificial Intelligence for Autonomous and Adaptive Agents
por: Lee, Sungwoo, et al.
Publicado: (2023)

A Biomimetic Way for Coral-Reef-Inspired Swarm Intelligence for Carbon-Neutral Wastewater Treatment
por: Messinis, Antonis
Publicado: (2025)

Automating the Search for Artificial Life with Foundation Models
por: Kumar, Akarsh, et al.
Publicado: (2024)

AutoOpt: A General Framework for Automatically Designing Metaheuristic Optimization Algorithms with Diverse Structures
por: Zhao, Qi, et al.
Publicado: (2022)

Dynamic Weight Adaptation in Spiking Neural Networks Inspired by Biological Homeostasis
por: Zhou, Yunduo, et al.
Publicado: (2025)

A Novel Ranking Scheme for the Performance Analysis of Stochastic Optimization Algorithms using the Principles of Severity
por: Chandrasekaran, Sowmya, et al.
Publicado: (2024)

Multi-objective Optimal Roadside Units Deployment in Urban Vehicular Networks
por: Guo, Weian, et al.
Publicado: (2024)

Predicting Confinement Effect of Carbon Fiber Reinforced Polymers on Strength of Concrete using Metaheuristics-based Artificial Neural Networks
por: Wahab, Sarmed, et al.
Publicado: (2023)

Sparse Spiking Neural Network: Exploiting Heterogeneity in Timescales for Pruning Recurrent SNN
por: Chakraborty, Biswadeep, et al.
Publicado: (2024)

A Novel Immune Algorithm for Multiparty Multiobjective Optimization
por: Chen, Kesheng, et al.
Publicado: (2026)

Growing Artificial Neural Networks for Control: the Role of Neuronal Diversity
por: Nisioti, Eleni, et al.
Publicado: (2024)

Automated Algorithm Design for Auto-Tuning Optimizers
por: Willemsen, Floris-Jan, et al.
Publicado: (2025)

Archive-based Single-Objective Evolutionary Algorithms for Submodular Optimization
por: Neumann, Frank, et al.
Publicado: (2024)

Comparing Optimization Algorithms Through the Lens of Search Behavior Analysis
por: Cenikj, Gjorgjina, et al.
Publicado: (2025)

Application of the Brain Drain Optimization Algorithm to the N-Queens Problem
por: Jolfaei, Sahar Ramezani, et al.
Publicado: (2025)

From Performance to Understanding: A Vision for Explainable Automated Algorithm Design
por: van Stein, Niki, et al.
Publicado: (2025)

Developmental Plasticity-inspired Adaptive Pruning for Deep Spiking and Artificial Neural Networks
por: Han, Bing, et al.
Publicado: (2022)