《Neural Computing & Applications》雜志的最新年發文量為1091篇。
這表明該刊在每年都會精選并發表一定數量的高質量文章，以保持其在計算機：人工智能領域的學術影響力。
該刊聚焦于計算機科學-計算機：人工智能領域的前沿研究，致力于推動該領域新技術和新知識的傳播與應用。同時它積極鼓勵研究人員詳細發表其高質量的實驗研究和理論成果。
該刊的平均審稿周期約為 約9.0個月 。
Neural Computing & Applications 雜志發文統計
文章名稱引用次數
- Feature selection via a novel chaotic crow search algorithm82
- Grey wolf optimizer: a review of recent variants and applications69
- Monarch butterfly optimization69
- Accurate photovoltaic power forecasting models using deep LSTM-RNN66
- Fault diagnosis of gearbox based on RBF-PF and particle swarm optimization wavelet neural network56
- An artificial neural network approach for under-reamed piles subjected to uplift forces in dry sand46
- Text classification based on deep belief network and softmax regression45
- A multi-verse optimizer approach for feature selection and optimizing SVM parameters based on a robust system architecture43
- Chaotic grasshopper optimization algorithm for global optimization43
- Artificial bee colony-based neural network for the prediction of the fundamental period of infilled frame structures41
國家/地區發文量
- CHINA MAINLAND1166
- India503
- Iran258
- USA212
- Pakistan154
- Turkey149
- Malaysia141
- England130
- Saudi Arabia127
- Spain120
