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Нүүр зураг

-д хадгалсан:

Номзүйн дэлгэрэнгүй
Үндсэн зохиолчид:	Zhang, Cheng, Sjarif, Nilam Nur Amir, Ibrahim, Roslina
Формат:	Preprint
Хэвлэсэн:	2023
Нөхцлүүд:	Machine Learning Neural and Evolutionary Computing
Онлайн хандалт:	https://arxiv.org/abs/2310.02090
Шошгууд:	Шошго нэмэх Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!

Ижил төстэй зүйлс

Effective Self-Attention-Based Deep Learning Model with Evolutionary Grid Search for Robust Wave Farm Energy Forecasting
-н: Dehkordi, Amin Abdollahi, зэрэг
Хэвлэсэн: (2025)

On the Interaction of Adaptive Population Control with Cumulative Step-Size Adaptation
-н: Omeradzic, Amir, зэрэг
Хэвлэсэн: (2024)

Smart Buildings Energy Consumption Forecasting using Adaptive Evolutionary Ensemble Learning Models
-н: Neshat, Mehdi, зэрэг
Хэвлэсэн: (2025)

A Step towards Interpretable Multimodal AI Models with MultiFIX
-н: Malafaia, Mafalda, зэрэг
Хэвлэсэн: (2025)

Comparative Analysis of Four Prominent Ant Colony Optimization Variants: Ant System, Rank-Based Ant System, Max-Min Ant System, and Ant Colony System
-н: Abdelmoaty, Ahmed Mohamed, зэрэг
Хэвлэсэн: (2024)

A Novel Denoising Technique and Deep Learning Based Hybrid Wind Speed Forecasting Model for Variable Terrain Conditions
-н: Malakar, Sourav, зэрэг
Хэвлэсэн: (2024)

A novel decision fusion approach for sale price prediction using Elastic Net and MOPSO
-н: Chaleshtori, Amir Eshaghi
Хэвлэсэн: (2024)

Optimizing PM2.5 Forecasting Accuracy with Hybrid Meta-Heuristic and Machine Learning Models
-н: Ghafariasl, Parviz, зэрэг
Хэвлэсэн: (2024)

Parametric Pareto Set Learning for Expensive Multi-Objective Optimization
-н: Cheng, Ji, зэрэг
Хэвлэсэн: (2025)

Deep Reinforcement Learning-Assisted Automated Operator Portfolio for Constrained Multi-objective Optimization
-н: Shao, Shuai, зэрэг
Хэвлэсэн: (2026)

Long-Sequence LSTM Modeling for NBA Game Outcome Prediction Using a Novel Multi-Season Dataset
-н: Rios, Charles, зэрэг
Хэвлэсэн: (2025)

Scaling Down Deep Learning with MNIST-1D
-н: Greydanus, Sam, зэрэг
Хэвлэсэн: (2020)

Automated Deep Learning for Load Forecasting
-н: Keisler, Julie, зэрэг
Хэвлэсэн: (2024)

An Experimental Study on Decomposition-Based Deep Ensemble Learning for Traffic Flow Forecasting
-н: Zhu, Qiyuan, зэрэг
Хэвлэсэн: (2024)

QL-LSTM: A Parameter-Efficient LSTM for Stable Long-Sequence Modeling
-н: Nti, Isaac Kofi
Хэвлэсэн: (2025)

Stochastic Volatility Modelling with LSTM Networks: A Hybrid Approach for S&P 500 Index Volatility Forecasting
-н: Perekhodko, Anna, зэрэг
Хэвлэсэн: (2025)

Aerial Reliable Collaborative Communications for Terrestrial Mobile Users via Evolutionary Multi-Objective Deep Reinforcement Learning
-н: Sun, Geng, зэрэг
Хэвлэсэн: (2025)

Spiking World Model with Multi-Compartment Neurons for Model-based Reinforcement Learning
-н: Sun, Yinqian, зэрэг
Хэвлэсэн: (2025)

Human-in-the-Loop Policy Optimization for Preference-Based Multi-Objective Reinforcement Learning
-н: Li, Ke, зэрэг
Хэвлэсэн: (2024)

A Universal Framework for Large-Scale Multi-Objective Optimization Based on Particle Drift and Diffusion
-н: Li, Jia-Cheng, зэрэг
Хэвлэсэн: (2025)

A Multi-objective Evolutionary Algorithm Based on Bi-population with Uniform Sampling for Neural Architecture Search
-н: Xue, Yu, зэрэг
Хэвлэсэн: (2026)

Directly Learning Stock Trading Strategies Through Profit Guided Loss Functions
-н: Kar, Devroop, зэрэг
Хэвлэсэн: (2025)

Annotated History of Modern AI and Deep Learning
-н: Schmidhuber, Juergen
Хэвлэсэн: (2022)

Dynamically Weighted Momentum with Adaptive Step Sizes for Efficient Deep Network Training
-н: Wang, Zhifeng, зэрэг
Хэвлэсэн: (2025)

Large Language Model-Based Benchmarking Experiment Settings for Evolutionary Multi-Objective Optimization
-н: Pang, Lie Meng, зэрэг
Хэвлэсэн: (2025)

First Mathematical Runtime Analyses of Multi-Objective Evolutionary Algorithms for Multi-Valued Decision Variables
-н: Li, Mingfeng, зэрэг
Хэвлэсэн: (2026)

Evolutionary Optimization of Deep Learning Agents for Sparrow Mahjong
-н: O'Connor, Jim, зэрэг
Хэвлэсэн: (2025)

Connectome-Guided Automatic Learning Rates for Deep Networks
-н: He, Peilin, зэрэг
Хэвлэсэн: (2025)

Deep Learning: Our Miraculous Year 1990-1991
-н: Schmidhuber, Juergen
Хэвлэсэн: (2020)

Mutation Strength Adaptation of the $(μ/μ_I, λ)$-ES for Large Population Sizes on the Sphere Function
-н: Omeradzic, Amir, зэрэг
Хэвлэсэн: (2024)

Deep Learning-Based Operators for Evolutionary Algorithms
-н: Shem-Tov, Eliad, зэрэг
Хэвлэсэн: (2024)

Time Series Forecasting of HIV/AIDS in the Philippines Using Deep Learning: Does COVID-19 Epidemic Matter?
-н: Aribe Jr., Sales G., зэрэг
Хэвлэсэн: (2024)

An Efficient Recommendation System in E-commerce using Passer learning optimization based on Bi-LSTM
-н: Abdalla, Hemn Barzan, зэрэг
Хэвлэсэн: (2023)

Deep Reinforcement Learning-Assisted Component Auto-Configuration of Differential Evolution Algorithm for Constrained Optimization: A Foundation Model
-н: Yang, Xu, зэрэг
Хэвлэсэн: (2025)

Surrogate-Assisted Evolution for Efficient Multi-branch Connection Design in Deep Neural Networks
-н: Stapleton, Fergal, зэрэг
Хэвлэсэн: (2025)

In-Simulation Testing of Deep Learning Vision Models in Autonomous Robotic Manipulators
-н: Humeniuk, Dmytro, зэрэг
Хэвлэсэн: (2024)

A First Step Towards Runtime Analysis of Evolutionary Neural Architecture Search
-н: Lv, Zeqiong, зэрэг
Хэвлэсэн: (2024)

Snail Homing and Mating Search Algorithm for Weight Optimization of Stepped-Transmission Shaft
-н: Saha, Kaustav, зэрэг
Хэвлэсэн: (2025)

Learning Gaussian Multi-Index Models with Gradient Flow: Time Complexity and Directional Convergence
-н: Şimşek, Berfin, зэрэг
Хэвлэсэн: (2024)

From Observation to Prediction: LSTM for Vehicle Lane Change Forecasting on Highway On/Off-Ramps
-н: Abouras, Mohamed, зэрэг
Хэвлэсэн: (2026)