標(biāo)題: Titlebook: Artificial Intelligence and Its Applications; Proceeding of the 2n Brahim Lejdel,Eliseo Clementini,Louai Alarabi Conference proceedings 202 [打印本頁] 作者: 自由 時(shí)間: 2025-3-21 19:19
書目名稱Artificial Intelligence and Its Applications影響因子(影響力)
書目名稱Artificial Intelligence and Its Applications影響因子(影響力)學(xué)科排名
書目名稱Artificial Intelligence and Its Applications網(wǎng)絡(luò)公開度
書目名稱Artificial Intelligence and Its Applications網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Artificial Intelligence and Its Applications被引頻次
書目名稱Artificial Intelligence and Its Applications被引頻次學(xué)科排名
書目名稱Artificial Intelligence and Its Applications年度引用
書目名稱Artificial Intelligence and Its Applications年度引用學(xué)科排名
書目名稱Artificial Intelligence and Its Applications讀者反饋
書目名稱Artificial Intelligence and Its Applications讀者反饋學(xué)科排名
作者: STERN 時(shí)間: 2025-3-21 23:49 作者: 牽索 時(shí)間: 2025-3-22 04:10 作者: candle 時(shí)間: 2025-3-22 06:15
The Pathology of Mathematics Education the strength and flexibility of a classifier when it comes to dealing with big data mining. Second, we will also test the execution speed for each classifier in complex cases; that is, when the classifier will not be sufficient to solve a particular problem in the context of big data mining, especi作者: 責(zé)任 時(shí)間: 2025-3-22 10:31 作者: Anticoagulants 時(shí)間: 2025-3-22 14:49 作者: 蟄伏 時(shí)間: 2025-3-22 19:38 作者: 馬具 時(shí)間: 2025-3-22 22:46 作者: PATRI 時(shí)間: 2025-3-23 02:32 作者: Ordnance 時(shí)間: 2025-3-23 06:18
Ramalingam Shanmugam,Karan P. Singhigher grade IMU at each (0.01 s) that was combined with DGPS data at each (1 s) in order to obtain the assumed true solution for the trajectory. The second one is real test data collected during land-vehicle trajectory. The implementation consists of three main algorithms that as well namely: Strapd作者: Esophagus 時(shí)間: 2025-3-23 11:54
A Decolonial Ethics-Aesthetics of Carech CNN-PA and RNN-PA that relies on users’ personal information and textual content for detecting user’s interests and preferences. We experimented our approach using a large Facebook dataset, and show how the deep learning approaches perform significantly better than the classical algorithms such a作者: 持續(xù) 時(shí)間: 2025-3-23 17:37
Dancing on the Edge of the Abysshe behavior of the Multi-Agent systems with interaction with SIEMENS Programmable Logic Controllers via OPC UA Protocol, during a Software-In-the-Loop “SIL” Test on a 3D Model of the Platform running on a separate Computer. The test assesses the behavior of the components of a typical Cyber-Physical作者: 任命 時(shí)間: 2025-3-23 21:53 作者: 和平主義 時(shí)間: 2025-3-23 23:25 作者: 不能仁慈 時(shí)間: 2025-3-24 04:06 作者: 好忠告人 時(shí)間: 2025-3-24 06:50 作者: 厚臉皮 時(shí)間: 2025-3-24 13:52 作者: LEVY 時(shí)間: 2025-3-24 15:16
Machine Learning Algorithms for Big Data Mining Processing: A Review, the strength and flexibility of a classifier when it comes to dealing with big data mining. Second, we will also test the execution speed for each classifier in complex cases; that is, when the classifier will not be sufficient to solve a particular problem in the context of big data mining, especi作者: 顧客 時(shí)間: 2025-3-24 22:24 作者: 繁忙 時(shí)間: 2025-3-25 01:21
Maximum Power Point Tracking of a Wind Turbine Based on Artificial Neural Networks and Fuzzy Logic PMSG) connected to a grid. The simulation results show the effectiveness of the proposed FLC and ANN controllers to achieve high tracking performance in the variable speed wind energy conversion systems (WECS).作者: Jargon 時(shí)間: 2025-3-25 04:37 作者: Antioxidant 時(shí)間: 2025-3-25 10:40 作者: 催眠藥 時(shí)間: 2025-3-25 12:24 作者: 游行 時(shí)間: 2025-3-25 16:21
GPS/IMU in Direct Configuration Based on Extended Kalman Filter Controlled by Degree of Observabiliigher grade IMU at each (0.01 s) that was combined with DGPS data at each (1 s) in order to obtain the assumed true solution for the trajectory. The second one is real test data collected during land-vehicle trajectory. The implementation consists of three main algorithms that as well namely: Strapd作者: indubitable 時(shí)間: 2025-3-25 22:31
,Deep Approach Based on User’s Profile Analysis for Capturing User’s Interests,ch CNN-PA and RNN-PA that relies on users’ personal information and textual content for detecting user’s interests and preferences. We experimented our approach using a large Facebook dataset, and show how the deep learning approaches perform significantly better than the classical algorithms such a作者: Manifest 時(shí)間: 2025-3-26 02:53
,Multi Agent Systems Based CPPS – An Industry 4.0 Test Case,he behavior of the Multi-Agent systems with interaction with SIEMENS Programmable Logic Controllers via OPC UA Protocol, during a Software-In-the-Loop “SIL” Test on a 3D Model of the Platform running on a separate Computer. The test assesses the behavior of the components of a typical Cyber-Physical作者: MARS 時(shí)間: 2025-3-26 06:26
,Ranking Social Media News Feeds: A Comparative Study of?Personalized and?Non-personalized Predictior users. Experimental results on . show that a single non-personalized model for all users is easy to manage and fine-tune, is less likely to overfit, and it addresses the problem of cold-start and inactive users. On the other hand, the personalized models we introduce allow personalized feature imp作者: 抱負(fù) 時(shí)間: 2025-3-26 10:18
,Machine Learning Based Indoor Localization Using Wi-Fi and?Smartphone in a Shopping Malls,ightforward solution to indoor positioning. Solutions based on Wi-Fi signal strength work in favor of the idea of controlling infrastructure costs. Our work attempts to explore other learning algorithms and make more robust trade-offs between accuracy and power. Our work also focuses on using classi作者: 影響帶來 時(shí)間: 2025-3-26 13:50
A Comparative Study Between the Two Applications of the Neural Network and Space Vector PWM for Dir-phase machines included in industrial application, this is due to its positive features among them is its high reliability and reduce both losses and rotor torque ripple..This paper aims to apply both techniques of artificial intelligence represented by the neural network algorithm NNA and the Spac作者: 蜈蚣 時(shí)間: 2025-3-26 18:00
Interval Versus Histogram of Symbolic Representation Based One-Class Classifier for Offline Handwri-ISR and OC-HSR, respectively, applied to the offline signature verification. Usually, symbolic verification models are built straightforward from the feature space. The proposed work explores an alternative approach based on the use of feature-dissimilarities generated from Curvelet Transform (CT) 作者: 新字 時(shí)間: 2025-3-27 00:11
Residual Neural Network for Predicting Super-Enhancers on Genome Scale, computer vision problems. It uses skip connections over some layer blocks to avoid vanishing gradient problem. Currently, many researches are focused to test and prove the efficiency of the ResNet on different domains such as genomics..In this paper, we propose a new ResNet model for predicting sup作者: 嗎啡 時(shí)間: 2025-3-27 01:47
Machine Learning Algorithms for Big Data Mining Processing: A Review,uires automation, which leads to serious consideration of the use of machine learning algorithms. Machine learning helps us make decisions if there is no right way to solve a problem identified in previous knowledge bases, and that is, too, one of the most widely used analysis and modeling tools for作者: 要素 時(shí)間: 2025-3-27 08:21 作者: MILL 時(shí)間: 2025-3-27 12:34 作者: 搖曳的微光 時(shí)間: 2025-3-27 15:33 作者: 一起 時(shí)間: 2025-3-27 19:09 作者: Myosin 時(shí)間: 2025-3-27 22:59 作者: 壟斷 時(shí)間: 2025-3-28 05:02
,Deep Neural Network Based TensorFlow Model for?IoT Lightweight Cipher Attack,rent limitations in size, storage memory, and power consumption limit its specific functionality in the secure transmission of sensitive information, where the development of lightweight ciphers responds adequately to these limitations. However, the conventional cryptanalysis of these modern ciphers作者: 單調(diào)性 時(shí)間: 2025-3-28 08:42
,Sentiment Analysis of?Algerian Dialect Using a?Deep Learning Approach,ment offers us a great interest for research, marketing and industry. With millions of comments and tweeting published every day, the information available on the Internet and in social media has become a gold mine for companies developing in their production, management and distribution. In this ar作者: Outspoken 時(shí)間: 2025-3-28 10:46
,Do We Need Change Detection for?Dynamic Optimization Problems?: A Survey,t be powerful enough to track new optima. For population based algorithms this is referred to as diversity loss problem. Furthermore, the memory of old optima becomes outdated and if not correctly dealt with, the evolution of the search process may be misguided. Recently, a new interesting trend in 作者: Employee 時(shí)間: 2025-3-28 18:17
GPS/IMU in Direct Configuration Based on Extended Kalman Filter Controlled by Degree of Observabili, and Global Positioning System (GPS). However, this INS-GPS system requires in generally a robust architecture such as an Extended Kalman Filter (EKF) approach in direct configuration, by reason of its properties of extensive evaluations of nonlinear equations. In addition, a practical approach for作者: 教唆 時(shí)間: 2025-3-28 19:37
Recognizing Arabic Handwritten Literal Amount Using Convolutional Neural Networks,on field where the challenges for the Arabic language are stilling. Despite their high importance and performances, for the best of our acknowledge, deep learning techniques have not been investigated in the context of Arabic handwritten literal amount recognition. The main aim of this paper is to i作者: insurrection 時(shí)間: 2025-3-28 23:18 作者: Rejuvenate 時(shí)間: 2025-3-29 06:43 作者: 輕打 時(shí)間: 2025-3-29 09:36
,Multi Agent Systems Based CPPS – An Industry 4.0 Test Case,trial world. This adoption is leading to the transformation of the mechatronic systems used in production into Cyber-Physical Production Systems. Such a concept is taking industrial Automation and computer integrated manufacturing to the next level. The massive migration of traditional production sy作者: liaison 時(shí)間: 2025-3-29 11:32
,Ranking Social Media News Feeds: A Comparative Study of?Personalized and?Non-personalized Predictioer, a single non-personalized model has been used to predict the relevance for all users. However, as user interests and preferences are different, we believe that using a personalized model for each user is crucial to refine the ranking. In this work, to predict the relevance of news feed updates a作者: 吸引人的花招 時(shí)間: 2025-3-29 15:49
Gilles Rouet,Stela Raytcheva,Thierry C?meightforward solution to indoor positioning. Solutions based on Wi-Fi signal strength work in favor of the idea of controlling infrastructure costs. Our work attempts to explore other learning algorithms and make more robust trade-offs between accuracy and power. Our work also focuses on using classi作者: caldron 時(shí)間: 2025-3-29 21:46 作者: Airtight 時(shí)間: 2025-3-30 03:46
Gilles Rouet,Stela Raytcheva,Thierry C?me-ISR and OC-HSR, respectively, applied to the offline signature verification. Usually, symbolic verification models are built straightforward from the feature space. The proposed work explores an alternative approach based on the use of feature-dissimilarities generated from Curvelet Transform (CT) 作者: Constitution 時(shí)間: 2025-3-30 07:16 作者: MIRE 時(shí)間: 2025-3-30 08:48 作者: SIT 時(shí)間: 2025-3-30 13:29 作者: Hla461 時(shí)間: 2025-3-30 19:51 作者: 集中營 時(shí)間: 2025-3-30 21:06 作者: 復(fù)習(xí) 時(shí)間: 2025-3-31 02:14
Mathematics Education: Is It Ethical?roximate to rigorous Models. According to its ability to preserve the complete accuracy of various types of physical sensors and its independence of sensors and platforms, it can be calculated with any coordination system. Nevertheless, the RFM coefficients are also known as rational polynomial coef作者: 惹人反感 時(shí)間: 2025-3-31 05:17 作者: 止痛藥 時(shí)間: 2025-3-31 12:05 作者: irreparable 時(shí)間: 2025-3-31 14:11 作者: backdrop 時(shí)間: 2025-3-31 18:21 作者: Noctambulant 時(shí)間: 2025-3-31 22:43 作者: 暴行 時(shí)間: 2025-4-1 02:01 作者: PAC 時(shí)間: 2025-4-1 06:56 作者: 啞巴 時(shí)間: 2025-4-1 12:28
A Decolonial Ethics-Aesthetics of Caren source for several domains such as business, marketing and politics..User’s profile describes its owner’s characteristics, where it contains several important personal information such as (age, sex, job title, level of education, etc.), which can help to improve the process of user’s interests ide
