Latest Publications & Patents on Neural Networks
This is our latest selection of worldwide publications and patents in english on Neural Networks, between many scientific online journals, classified and focused on neural network, artificial neuron, epoch, neural architecture, machine learning, deep learning and support vector machine.
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A Novel Approach for Shear Wave Velocity Prediction Utilizing Well Logging
Published on 2025-02-22 by Jiayi Li, Yaoting Lin, Zhixian Gui, Peng Wang @MDPI
Abstract: Shear wave velocity prediction is critical for applications in petrophysics, reservoir characterization, and unconventional energy resource development. While empirical formulas and theoretical rock physics models offer solutions, they are often limited by geological complexity, high cost, and computational inefficiency. After the emergence of deep learning methods, a series of new approaches have been provided to tackle these problems. In this study, a novel Inception–attention&am[...]
Our summary: A novel hybrid network approach is proposed for shear wave velocity prediction using well logging data, achieving superior performance compared to standalone networks. This approach integrates Inception, attention mechanisms, and BiLSTM to enhance prediction accuracy and stability, demonstrating robustness in handling complex logging data.
shear wave velocity prediction, well logging, deep learning, hybrid network
Publication
A Hybrid Deep Learning Approach
Published on 2025-02-22 by Noor Ul Ain, Muhammad Sardaraz, Muhammad Tahir, Mohamed W. Abo Elsoud, Abdullah Alourani @MDPI
Abstract: The Internet of Things (IoT) has revolutionized many domains. Due to the growing interconnectivity of IoT networks, several security challenges persist that need to be addressed. This research presents the application of deep learning techniques for Distributed Denial-of-Service (DDoS) attack detection in IoT networks. This study assesses the performance of various deep learning models, including Latent Autoencoders, LSTM Autoencoders, and convolutional neural networks (CNNs), for DDoS attack de[...]
Our summary: Application of deep learning techniques for DDoS attack detection in IoT networks using a novel hybrid model. Performance assessment of various deep learning models. Enhanced performance of the proposed hybrid model in addressing complex attack patterns within IoT networks.
Deep Learning, Internet of Things, DDoS attack detection, Hybrid model
Publication
A Spatiotemporal-Adaptive-Network-Based Method for Predicting Axial Forces in Assembly Steel Struts with Servo System of Foundation Pits
Published on 2025-02-22 by Weiwei Liu, Jianchao Sheng, Jian Zhou, Jinbo Fu, Wangjing Yao, Kuan Chang, Zhe Wang @MDPI
Abstract: The axial force in assembly steel struts with servo systems is a critical indicator of stability in foundation pit support systems. Due to its high sensitivity to temperature variations and direct influence on the lateral deformation of the foundation pit enclosure structure, accurate prediction is essential for safety monitoring and early warning. This study proposes a novel method for predicting the axial force in assembly steel struts with servo systems based on a spatiotemporal adaptive netw[...]
Our summary: Novel method for predicting axial forces in assembly steel struts with servo systems based on spatiotemporal adaptive network. Historical data fed into LSTM network, self-attention mechanism captures global dependencies, CNN extracts local spatial features, and excavation data used to derive stratification-related features for more accurate predictions. Validation on deep foundation pit data shows improved performance.
LSTM network, self-attention mechanism, convolutional neural network, spatiotemporal adaptive network
Publication
A Multidisciplinary Case Study of Patents
Published on 2025-02-22 by Raj Bridgelall @MDPI
Abstract: The exponential growth of patent datasets poses a significant challenge in filtering relevant documents for research and innovation. Traditional semantic search methods based on keywords often fail to capture the complexity and variability in multidisciplinary terminology, leading to inefficiencies. This study addresses the problem by systematically evaluating supervised and unsupervised machine learning (ML) techniques for document relevance filtering across five technology domains: solid-state[...]
Our summary: This study evaluates supervised and unsupervised machine learning techniques for document relevance filtering in patents across five technology domains, showing that supervised models outperform unsupervised methods and offering a practical framework for optimizing filtering processes.
patents, machine learning, document relevance filtering, technology domains
Publication
New Method for Improving Tracking Accuracy of Aero-Engine On-Board Model Based on Separability Index and Reverse Searching
Published on 2025-02-22 by Hui Li, Yingqing Guo, Xinyu Ren @MDPI
Abstract: Throughout its service life, an aero-engine will experience a series of health conditions due to the inevitable performance degradation of its major components, and characteristics will deviate from their initial states. For improving tracking accuracy of the self-tunning on-board engine model on the engine output variables throughout the engine service life, a new method based on the separability index and reverse search algorithm was proposed in this paper. By using this method, a qualified tr[...]
Our summary: New method proposed for improving tracking accuracy of on-board aero-engine model throughout service life, based on separability index and reverse search algorithm. Higher accuracy maintained in engine life compared to sample memory factors method. Real-time monitoring of engine gas path parameters possible with training set center generated by proposed method.
tracking accuracy, aero-engine, separability index, reverse searching
Publication
Actual Truck Arrival Prediction at a Container Terminal with the Truck Appointment System Based on the Long Short-Term Memory and Transformer Model
Published on 2025-02-21 by Mengzhi Ma, Xianglong Li, Houming Fan, Li Qin, Liming Wei @MDPI
Abstract: The implementation of the truck appointment system (TAS) in various ports shows that it can effectively reduce congestion and enhance resource utilization. However, uncertain factors such as traffic and weather conditions usually prevent the external trucks from arriving at the port on time according to the appointed period for container pickup and delivery operations. Comprehensively considering the significant factors associated with truck appointment no-shows, this paper proposes a deep learn[...]
Our summary: Actual truck arrival prediction using a deep learning model combining LSTM and transformer architectures shows superior performance in reducing congestion and enhancing resource utilization at container terminals.
Truck Appointment System, Long Short-Term Memory, Transformer Model, Deep Learning
Publication
Fluid flow simulation
Patent published on the 2025-02-19 in EP under Ref EP4510034 by ROLLS ROYCE PLC [GB] (Loh Jessica Sher En [gb], Arafat Naheed Anjum [gb], Kong Wai Kin Adams [gb], Chan Wai Lee [gb], Conduit Bryce D [gb], Lim Wei Xan [gb], Oo Thant Zin [gb])
Abstract: A method of using a computer implemented neural network for a simulation of aerodynamic performance of a technical object having a geometry, the method comprising:Training the neural network using a plurality of sets of encodings of pre-computed computational fluid dynamics, CFD, outputs, wherein the training is generated using inputs comprising:a geometry of at least one training technical object;spatial locations of input nodes of the neural network as node attributes;a relationship between th[...]
Our summary: Method using neural network for aerodynamic simulation of technical objects, training with pre-computed CFD outputs, generating predicted aerodynamic performance.
Fluid flow simulation, neural network, aerodynamic performance, computational fluid dynamics
Patent
Method, system and computer readable medium for assisting or enhancing 5g radio planning
Patent published on the 2025-02-19 in EP under Ref EP4510672 by UNIV CATALUNYA POLITECNICA [ES] (Almasan Paul [es], SuÁrez-varela JosÉ [es], Lutu Andra [es], Cabellos-aparicio Albert [es], Barlet-ros Pere [es])
Abstract: A method, system, and computer programs for assisting or enhancing 5G radio planning are proposed. The method comprises obtaining information about a new deployment of 5G-generation radio cells in a given area; obtaining information about previous-generation radio cells already deployed in the given area, and computing a plurality of key performance indicators, KPI, of the previous-generation radio cells by processing the obtained information, providing a plurality of KPI previous-generation rec[...]
Our summary: Method, system, and computer programs for assisting or enhancing 5G radio planning by obtaining information about new and previous-generation radio cells, computing key performance indicators, generating representations using deep learning, and producing KPIs with a neural network model.
5G, radio planning, deep learning, neural network
Patent
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