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2023 IEEE International Conference on Sensors, Electronics and computer Engineering, ICSECE 2023

作者： Yue, Junrong Jining University School of Mathematics and Computer Application Technology Jining China

ISBN: (纸本)9798350313734

This study aims to optimize the dispatching operation and control of power system to reduce the increased operation cost caused by the uncertainty and volatility of wind power. To achieve this goal, a data model is proposed based on GA genetic algorithm optimized BP neural network. It can predict generator speed and perform network-wide power balancing, thus ensuring the safe and stable operation of the system. The study proceeds in three stages. First, data cleaning and pre-processing are performed on the data obtained from Kaggle. Second, a BP neural network model with 11 input indicators, such as the temperature of generator winding 1 and 2, rotor speed, and hub temperature, is constructed. The output of the model is the generator speed. The weights and thresholds of the BP neural network are optimized by genetic algorithm. Finally, we verify the effectiveness of our approach. By comparing the prediction results based on the BP model only, we demonstrate that the root mean square error of the proposed method is reduced by 31.28%. This confirms that the proposed model is an effective and feasible method for predicting generator speed. In summary, the proposed data model based on GA genetic algorithm optimized BP neural network can provide improved control over wind power variability and reduce operational costs. The results of this study pave the way for further research and application of advanced modeling and optimization techniques in power systems. © 2023 IEEE.

关键词： Neural networks

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Enhancement of Farming Using IoT Based Unmanned Aerial Vehicles 2

Enhancement of Farming Using IoT Based Unmanned Aerial Vehic...

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2nd International Conference on Disruptive Technologies, ICDT 2024

作者： Tiwari, Vanshika Prakash, Shiva Madan Mohan Malaviya University of Technology Department of Information Technology and Computer Application Uttar Pradesh Gorakhpur273010 India

ISBN: (纸本)9798350371055

The agriculture sector faces the pressing challenge of increasing food production while optimizing resource use and minimizing environmental impact. One promising solution to address these challenges is the integration of Internet of Things (IoT) based Unmanned Aerial Vehicles (UAVs) into farming practices. This research paper explores the potential benefits, challenges and implications of using IoT-based UAVs in agriculture. It examines how this technology can enhance farming by providing real-time data, precision agriculture capabilities and improved resource management. There are detecting diseases in agriculture field to reduce background noise using the Median filters, Temporal filters. This helps to remove noise and vestiges caused by the movement of the drone or the target factory. © 2024 IEEE.

关键词： Image Processing Internet of Things (IoT) Median Filter Temporal Filter Unmanned Aerial Vehicles (UAVs)

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A Survey of Complex Network Representation Learning Methods 23

A Survey of Complex Network Representation Learning Methods

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7th International Conference on High Performance Compilation, Computing and Communications, HP3C 2023

作者： Wang, Keke Zhu, Yu Huang, Jiangqiang Wang, Xiaoying Department of Computer Technology and Application Qinghai University Xining810000 China

ISBN: (纸本)9781450399883

Network representation learning is a technique that embeds the nodes in a network into a low-dimensional vector space, providing strong support for network analysis tasks such as node classification, link prediction, and community detection. This paper provides a summary of the research in the field of network representation learning in recent years. Firstly, the definition of network representation learning is introduced. Then, traditional network representation learning methods are presented, including matrix factorization-based methods, random walk-based methods, and neural network-based methods. However, traditional network representation learning methods can only be applicable to the traditional networks abstracted as the graphs and not applicable to the hypernetworks abstracted as the hypergraphs. Therefore, this paper also introduces hypernetwork representation learning methods, including homogeneous hypernetwork representation learning and heterogeneous hypernetwork representation learning. Finally, this paper summarizes future research directions in network representation learning. © 2023 ACM.

关键词： Vector spaces

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Behavioral Customer Segmentation For Subscription 3

Behavioral Customer Segmentation For Subscription

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3rd IEEE Asian Conference on Innovation in technology, ASIANCON 2023

作者： Mali, Mayank Mangaonkar, Nikhita Sardar Patel Institute of Technology Masters of Computer Application Mumbai India

ISBN: (纸本)9798350302288

This research paper addresses the challenge faced by mobile app developers in converting free app users to premium users. Specifically, we aim to predict customer interest in the premium version of a mobile app by analyzing user behavior and app usage patterns. To accomplish this, we use a dataset of over 50,000 app users and employ machine learning algorithms to develop a model that predicts subscription conversion with high accuracy. Our study finds that features such as total time spent on the app, frequency of app usage, and user engagement with specific features of the app are strong predictors of subscription conversion. We also evaluate several machine learning classifiers and find that the XGBoost classifier outperforms other algorithms in terms of accuracy and precision. Our findings provide insights into customer behavior and highlight the factors that influence subscription conversion, allowing app developers to focus on improving user engagement and providing value-added features to increase the likelihood of subscription conversion. © 2023 IEEE.

关键词： Machine learning

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Multivariate Deep Learning for Reconstruction of Spatial Missing Climate Data 3

Multivariate Deep Learning for Reconstruction of Spatial Mis...

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3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing, AIAHPC 2023

作者： Yao, Ziqiang Wu, Li Huang, Jianqia Wang, Xiaoying Department of Computer Technology and Application Qinghai University Xining810016 China

ISBN: (数字)9781510666580

ISBN: (纸本)9781510666573

Complete meteorological data is essential for meteorological research. However, due to sensor failure or occlusion, data loss always occurs. In order to deal with this problem, geoscience often uses Kriging and other traditional interpolation methods. Nevertheless, because the traditional method only considers the existing data, it cannot provide accurate reconstruction results when the spatial missing rate is large. Inspired by image inpainting algorithms, we propose a new deep learning method that combines other variables related to missing meteorological variables to provide more effective information for missing regions, and proves the good effect of the method through a series of experiments. To illustrate that our method can maintain good performance under different missing rates, we use the reanalysis data of the European Centre for Medium-Range Weather Forecasts to create a data set with three different missing rates of 30%, 50%, and 70% through the artificial mask. Under different missing rates, the average RMSE of the method based on deep learning decreased by 77% and 31% respectively compared with Kriging and DINEOF. In addition, by combining relevant variables, the accuracy of the deep learning model can be further improved by about 16%. © 2023 SPIE.

关键词： Kriging

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Multi Terminal Adaptive Layout Based on HTML 5 and CSS3 1

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作者： Zheng, Wei Zhou, Qiang Ou, Wenjisi Department of Computer Technology Jiangxi Vocational and Technical College of Information Application Nanchang330043 China

ISBN: (数字)9789819719792

ISBN: (纸本)9789819719785

Layout is a key link in web page design. In addition to PC, there are a large number of mobile terminals for accessing web pages. When the fixed layout is migrated to the mobile terminal, the user experience is likely to be insufficient. For these devices with different resolutions, CSS3 technology adopts different methods to solve the problem. This paper proposes a responsive layout solution based on HTML 5+ CSS3. First, use HTML5 semantic structural tags to transform DIV tags with semantic requirements in fixed layouts. Then through CSS3's media query and flexible layout, we design the responsive layout of the web page layout, and set the responsive code for pictures and text. The experimental research shows that this scheme realizes the free switching and smooth transition of web pages between different terminals and improves the user experience. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Data fusion

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Development of educational game as a media to raise public awareness of illegal animal trafficking issue in Indonesia 9th

Development of educational game as a media to raise public a...

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9th International Conference on computer Science and Computational Intelligence, ICCSCI 2024

作者： William, Jonathan Ahmadi, Khalid Fajar, Muhamad Game Application & Technology Program Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

The amount of illegal wildlife trade cases increases every year in Indonesia. This causes some unique Indonesian wildlife to become endangered or even extinct. Therefore, the purpose of this research is to raise public awareness to illegal wildlife trade issue by using a game as its media to reduce the number of cases of illegal wildlife trade in Indonesia. The game made in this research will be developed using the GDLC development method and 2021.3.11f1 version of Unity as its game engine. To evaluate the game that has been developed in this research, a comparation to other related games is conducted and resulted in the game that has been developed in this research is significantly better than other related games in Challenge, Learnability and Concentration aspects (p © 2024 The Authors.

关键词： Invertebrates

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Intelligent hierarchical federated learning system based on semi-asynchronous and scheduled synchronous control strategies in satellite network

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Autonomous Intelligent Systems 2025年第1期5卷 1-14页

作者： Mei, Qiang Huang, Rui Li, Duo Li, Jingyi Shi, Nan Du, Mei Zhong, Yingkang Tian, Chunqi Operations Services Department China Satellite Network Application Co. Ltd Beijing100089 China College of Computer Science and Technology Tongji University Shanghai201804 China

Federated learning (FL) is a technology that allows multiple devices to collaboratively train a global model without sharing original data, which is a hot topic in distributed intelligent systems. Combined with satellite network, FL can overcome the geographical limitation and achieve broader applications. However, it also faces the issues such as straggler effect, unreliable network environments and non-independent and identically distributed (Non-IID) samples. To address these problems, we propose an intelligent hierarchical FL system based on semi-asynchronous and scheduled synchronous control strategies in cloud-edge-client structure for satellite network. Our intelligent system effectively handles multiple client requests by distributing the communication load of the central cloud to various edge clouds. Additionally, the cloud server selection algorithm and the edge-client semi-asynchronous control strategy minimize clients’ waiting time, improving the overall efficiency of the FL process. Furthermore, the center-edge scheduled synchronous control strategy ensures the timeliness of partial models. Based on the experiment results, our proposed intelligent hierarchical FL system demonstrates a distinct advantage in global accuracy over traditional FedAvg, achieving 2% higher global accuracy within the same time frame and reducing 52% training time to achieve the target accuracy. © The Author(s) 2025.

关键词： Federated learning

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Urban Growth Estimation of Moradabad City Using Sentinel-2 Images

Urban Growth Estimation of Moradabad City Using Sentinel-2 I...

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2024 International Conference on Artificial Intelligence and Emerging technology, Global AI Summit 2024

作者： Srivastava, Saurabh Ahmed, Tasneem Kumar, Rajeev Moradabad Institute of Technology Department of Computer Science & Engineering Moradabad India Integral University Department of Computer Application Lucknow India

ISBN: (纸本)9798350379716

Accurate monitoring and assessment are necessary due to the enormous challenges posed by rapid urbanization to sustainable development and resource management. This study utilizes Sentinel-2 satellite images of Moradabad City, located in Uttar Pradesh, India, to analyze urban growth through a machine learning approach. Sentinel-2 imagery is widely used for land cover monitoring, and images from 2017 and 2023 were selected to assess the rapid expansion of urbanization. Various techniques, including SVM, ANN and minimum distance (MD), were employed for land surface classification. Among these, SVM produced the most reliable results for estimating urban areas, based on both the Kappa coefficient (Kc) and overall accuracy (O.A.). The SVM estimates that in 2017 about 8.308% of the region was classified as an urban area, and from 2023 that number had increased to about 11.64%, which could be a serious concern for Moradabad city's residents. The motivation behind this study to explore the potential applications of machine learning methods for small-scale urban dynamics monitoring and analysis through satellite image analysis. The research advances knowledge of urbanization processes and offers insightful advice for sustainable urban growth in quickly expanding places. © 2024 IEEE.

关键词： ANN MD Sentinel-2 SVM Urban Area Estimation Urban Growth estimation

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Player evaluation and learning outcomes of "NusaVenturas": A serious game for enhancing player knowledge and interest in Indonesian traditional foods 9th

Player evaluation and learning outcomes of "NusaVenturas": A...

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9th International Conference on computer Science and Computational Intelligence, ICCSCI 2024

作者： Sanjaya, Vito Sebastian Tanoto, Nicholas Valenthinus Tandinata, Nicholas Ramdhan, Dimas Game Application & Technology Program Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

The popularity of Indonesian traditional food has been declining due to the increasing influence of foreign cuisine. This study presents the development method that combining Game Development Life Cycle (GDLC) with Experiential Game Learning Design Framework and evaluation of a serious game "NusaVenturas" using usability, learning outcome, and Game Experience Questionnaire (GEQ) that designed to introduce, promote interest, educate, and preserve knowledge of Indonesian traditional foods. "NusaVenturas" is a unique 2D serious game that integrates puzzle-platformer elements with time-management cooking mechanics. The study involved 37 participants aged 18 to 23. Evaluation results indicate that "NusaVenturas" significantly enhances players' knowledge of Indonesian traditional foods, with statistical analysis confirming the significance of the findings. © 2024 The Authors.

关键词： Food ingredients

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