標(biāo)題: Titlebook: Advanced Intelligent Computing Technology and Applications; 19th International C De-Shuang Huang,Prashan Premaratne,Abir Hussain Conference [打印本頁] 作者: cherub 時間: 2025-3-21 19:17
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書目名稱Advanced Intelligent Computing Technology and Applications網(wǎng)絡(luò)公開度學(xué)科排名
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書目名稱Advanced Intelligent Computing Technology and Applications讀者反饋
書目名稱Advanced Intelligent Computing Technology and Applications讀者反饋學(xué)科排名
作者: Radiation 時間: 2025-3-21 23:39 作者: 確定方向 時間: 2025-3-22 02:00 作者: TOXIN 時間: 2025-3-22 04:33 作者: amygdala 時間: 2025-3-22 09:17
RNL: A Robust and Highly-Efficient Model for Time-Aware Web Service QoS Predictionctly on the encrypted data, without needing a preceding decryption operation. The most important condition in homomorphic encryption is that the value achieved by decrypting the result obtained by applying the calculations over the encrypted data must be the same as the value achieved by applying th作者: 損壞 時間: 2025-3-22 16:49
A Time-Aware Graph Attention Network for Temporal Knowledge Graphs Reasoninge right methods for writing advanced cryptographic algorithms, such as elliptic curve cryptography algorithms, lattice-based cryptography, searchable encryption, and homomorphic encryption. You‘ll also examine internal cryptographic mechanisms and discover common ways in which the algorithms can be 作者: 燕麥 時間: 2025-3-22 20:20 作者: IOTA 時間: 2025-3-22 21:23
Information Extraction System for Invoices and Receiptsat underpins Power BI–to create reusable measures to deliver finely-crafted custom calculations in your dashboards..This book starts off teaching you how to define and enhance the core structures of your data model to make it a true semantic layer that transforms complex data into familiar business 作者: 低能兒 時間: 2025-3-23 02:41
Missing Data Analysis and Soil Compressive Modulus Estimation via Bayesian Evolutionary Treessis Expressions),?the formula language used in Power BI—Microsoft’s leading self-service business intelligence application—and covers other products such as PowerPivot and SQL Server Analysis Services Tabular. You will learn how to leverage the advanced applications of DAX to solve complex tasks..Of作者: 無可爭辯 時間: 2025-3-23 07:45 作者: 分解 時間: 2025-3-23 10:21 作者: 浮雕 時間: 2025-3-23 17:02
Dynamic Label Propagation Density Peak Clustering Based on the Tissue-Like P Systemsa is correct. It has no way of . that this is the case. In fact, it could have been duped or spoofed in a variety of ways, such as the query response may have been supplied from a poisoned zone file, or the query may have been intercepted and bad data substituted in the response. Another possibility作者: Anticoagulant 時間: 2025-3-23 21:45
TAP-AHGNN: An Attention-Based Heterogeneous Graph Neural Network for Service Recommendation on Triggtion strategies, as well as the impact of single-instance stGood backup and recovery strategies are key to the health of any organization. Medium- to very-large-scale systems administrators have to protect large amounts of critical data as well as design backup solutions that are scalable and optimi作者: 颶風(fēng) 時間: 2025-3-24 01:55 作者: 周年紀(jì)念日 時間: 2025-3-24 02:49 作者: 小故事 時間: 2025-3-24 09:51 作者: Aggressive 時間: 2025-3-24 10:48
K-means Based Transfer Learning Algorithmperationalize the migration of a database application from your organization’s data center to Microsoft’s Azure cloud platform..Data modernization and migration is a technologically complex endeavor that can also be taxing from a leadership and operational standpoint. This book covers not only the t作者: Chromatic 時間: 2025-3-24 15:20
HSIC Induced LncRNA Feature Selectioninvent new deep learning architectures and solutions on your own..Pro Deep Learning with TensorFlow.?provides practical, hands-on expertise so you can learn deep learning from scratch and deploy meaningful deep learning solutions. This book will allow you to get up to speed quickly using TensorFlow 作者: corporate 時間: 2025-3-24 20:59
2D-DLPP Algorithm Based on SPD Manifold Tangent Space complex structures in language and deriving insights and actions from it are crucial from an artificial intelligence perspective. In several domains, the importance of natural language processing is paramount and ever growing, as digital information in the form of language is ubiquitous. Applicatio作者: 單純 時間: 2025-3-25 01:57 作者: 切掉 時間: 2025-3-25 05:12 作者: STING 時間: 2025-3-25 09:45
Hyperbolic Geometry of Gyrovector Spaces,ject, timestamp). The TKG reasoning task aims to predict missing entity, i.e., “?” in the quadruple (entity, relation, ?, future time) from known facts. Although existing temporal knowledge graph reasoning models consider the quadruple information of each timestamp separately, they fail to fully exp作者: ostensible 時間: 2025-3-25 12:45 作者: bypass 時間: 2025-3-25 18:09 作者: MILK 時間: 2025-3-25 22:42
Thomas Precession: The Missing Link,accurately and efficiently. However, it has become impractical for humans to extract the data manually, as it is labor-intensive and time-consuming. Digital documents contain various components such as tables, key-value pairs and figures. Existing optical character recognition (OCR) methods can reco作者: Optic-Disk 時間: 2025-3-26 03:15 作者: sultry 時間: 2025-3-26 04:47 作者: PUT 時間: 2025-3-26 11:19
https://doi.org/10.1007/978-3-030-46831-6gers, and accidents, which is significant in maintaining the target system’s health and stability. Recent years have witnessed a long list of unsupervised time-series anomaly detection models that can only work without any control after deployment. This motivates us to consider an intriguing questio作者: Canary 時間: 2025-3-26 14:51 作者: BIDE 時間: 2025-3-26 16:57
Constantin Iordachi,Aristotle Kallisng if-trigger-then-action rules. However, with the increasing number of IoT services, specifying trigger and action services to compose TAP rules becomes progressively challenging for users due to the vast search space. To facilitate users in programming, a novel method named TAP-AHGNN is proposed t作者: cinder 時間: 2025-3-26 21:23
Neferti X. M. Tadiar,Angela Y. Davisr time. Online data-stream outlier detection can indeed be more difficult and challenging. This is because new data points are continuously arriving, and the outlier detection algorithm must process them in real-time. Our idea is to use online evolving spiking neural network classifier and dynamic o作者: Aggrandize 時間: 2025-3-27 01:52
https://doi.org/10.1007/978-1-4039-8261-2r system. With the development of social production, the electricity consumption in people’s daily life, factories and enterprises is continuously increasing, it also increases the difficulty of electric load forecasting. Traditional methods are difficult to analyze the huge and complex electricity 作者: Explicate 時間: 2025-3-27 08:38 作者: 方舟 時間: 2025-3-27 11:10
https://doi.org/10.1007/978-1-4039-8261-2f cancer can be predicted by analyzing lncRNAs. However, lncRNA is characterized by a limited amount of data samples and a large number of expression levels of gene features, where there exist much redundancy. It results in difficulty in cancer predicting. To solve the problem, this paper proposes a作者: 爆炸 時間: 2025-3-27 15:28
https://doi.org/10.1007/978-1-4039-8261-2 propose a new algorithm based on the manifold tangent space, called the manifold tangent space-based 2D-DLPP algorithm. This algorithm embeds the covariance matrix into the tangent space of the SPD manifold and utilizes Log-Euclidean Metric Learning (LEM) to fully extract feature information, thus 作者: Canyon 時間: 2025-3-27 19:13
Advanced Intelligent Computing Technology and Applications978-981-99-4752-2Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 憲法沒有 時間: 2025-3-27 23:19
https://doi.org/10.1007/978-981-99-4752-2Evolutionary Computation and Learning; Swarm Intelligence and Optimization; Information Security; Theor作者: Grievance 時間: 2025-3-28 05:52 作者: 是剝皮 時間: 2025-3-28 06:19 作者: FRAUD 時間: 2025-3-28 12:26
https://doi.org/10.1007/978-1-4039-8261-2er fit the non-convex distribution of data (MKTL, Multi-core K-means Transfer Learning). The experimental results show that MKTL achieves the best average accuracy in 3 datasets. Compared with the original methods (kNN, TCA, GFK, JDA), the performance of MKTL is improved by 2.5?~?12.8 percentage in high computational efficiency.作者: magnanimity 時間: 2025-3-28 14:45 作者: frenzy 時間: 2025-3-28 20:20 作者: 傲慢人 時間: 2025-3-29 00:06 作者: vitreous-humor 時間: 2025-3-29 06:31
Conference proceedings 2023proceedings of the 19th International Conference on Intelligent Computing, ICIC 2023, held in Zhengzhou, China, in August 2023..The 337 full papers of the three proceedings volumes were carefully reviewed and selected from 828 submissions..This year, the conference concentrated mainly on the theorie作者: 控訴 時間: 2025-3-29 10:04
Neferti X. M. Tadiar,Angela Y. Davis moving window of time. Our approach is found superior in terms of effectiveness than the other solutions provided in the literature when applied to data streams from the Numenta Anomaly Benchmark repository.作者: 努力趕上 時間: 2025-3-29 14:10
Conference proceedings 2023ions. Therefore, the theme for this conference was "Advanced Intelligent Computing Technology and Applications". Papers that focused on this theme were solicited, addressing theories, methodologies, and applications in science and technology..作者: climax 時間: 2025-3-29 19:14
0302-9743 h applications. Therefore, the theme for this conference was "Advanced Intelligent Computing Technology and Applications". Papers that focused on this theme were solicited, addressing theories, methodologies, and applications in science and technology..978-981-99-4751-5978-981-99-4752-2Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: Albinism 時間: 2025-3-29 21:45
Hyperbolic Geometry of Gyrovector Spaces,state on speed is fitted by a two-dimensional Gaussian distribution. Finally, the thresholds are generated according to the properties of two-dimensional Gaussian distribution. The rationality of the traffic state thresholds is verified by experiments. Also, the traffic state identification accuracy作者: Motilin 時間: 2025-3-30 00:46
https://doi.org/10.1007/0-306-47134-5adopting Cauchy loss to build objective function for achieving strong robustness and high prediction accuracy, b) applying an alternating direction method of multi-pliers (ADMM) principle to design parameters learning scheme for obtaining high computational efficiency. Experimental results on two ti作者: 正式演說 時間: 2025-3-30 04:18 作者: 泥沼 時間: 2025-3-30 09:14 作者: 粗俗人 時間: 2025-3-30 13:28
,Gyrooprations — the ,(2, ,) Approach,sed learning scheme for solving the learning objective on the premise of fast convergence; c) implementing self-adaptation of the model’s multiple hyper-parameters via the .ree-structured of .arzen .stimators (TPE) algorithm, thus enabling its high scalability. Empirical studies on four UWNs from re作者: 親愛 時間: 2025-3-30 20:06 作者: 體貼 時間: 2025-3-30 22:42 作者: 頭腦冷靜 時間: 2025-3-31 03:38 作者: 身體萌芽 時間: 2025-3-31 08:10
https://doi.org/10.1007/978-3-030-46831-6le of unsupervised anomaly scoring, and by leveraging the derived anomaly scores, we devise two reward strategies. The learning process is guided by these reward strategies, during which the agent is encouraged to explore possible anomalies hidden in the unlabeled set. These potential anomalies are 作者: 柔聲地說 時間: 2025-3-31 09:27
https://doi.org/10.1007/978-3-030-46831-6erations using a dynamic label propagation assignment strategy. Comparative experiments are carried out on seven datasets, and the consequences show that the proposed method has a good clustering performance.作者: sinoatrial-node 時間: 2025-3-31 14:51
Constantin Iordachi,Aristotle Kallis integration of multiple types of features. With the two modules mentioned before, the final representations of services can capture both semantic and structural information, which helps generate better recommendation results. Experiments on the real-world dataset demonstrate that TAP-AHGNN outperfo作者: 單純 時間: 2025-3-31 20:40 作者: 鄙視 時間: 2025-3-31 23:22
Multivariate Time Series Anomaly Detection Method Based on mTranAD978-1-4302-0277-6作者: Encapsulate 時間: 2025-4-1 02:41
Advanced Intelligent Computing Technology and Applications19th International C
