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Optimal Deep Canonically Correlated Autoencoder-Enabled Prediction Model for Customer Churn Prediction

computers, Materials & Continua 2022年第11期73卷 3757-3769页

作者： Olfat M.Mirza GJose Moses R.Rajender E.Laxmi Lydia Seifedine Kadry Cheadchai Me-Ead Orawit Thinnukool Department of Computer Science College of Computers and Information SystemsUmm Al-Qura UniversityMakkahSaudi Arabia Department of Computer Science Engineering Malla Reddy Engineering College500100India Department of Computer Science Engineering Lendi Institute of Engineering&TechnologyDenkada535005India Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Applied Data Science Noroff University CollegeNorway Program in Statistics and Information Management Faculty of ScienceMaejo UniversityChiang Mai50290Thailand Department of Modern Management and Information Technology College of Arts Media and TechnologyChiang Mai UniversityChiang Mai50200Thailand

Presently,customer retention is essential for reducing customer churn in telecommunication *** churn prediction(CCP)is important to predict the possibility of customer retention in the quality of *** risks of customer churn also get essential,the rise of machine learning(ML)models can be employed to investigate the characteristics of customer ***,deep learning(DL)models help in prediction of the customer behavior based characteristic *** the DL models necessitate hyperparameter modelling and effort,the process is difficult for research communities and business *** this view,this study designs an optimal deep canonically correlated autoencoder based prediction(ODCCAEP)model for competitive customer dependent application *** addition,the O-DCCAEP method purposes for determining the churning nature of the *** O-DCCAEP technique encompasses preprocessing,classification,and hyperparameter ***,the DCCAE model is employed to classify the churners or ***,the hyperparameter optimization of the DCCAE technique occurs utilizing the deer hunting optimization algorithm(DHOA).The experimental evaluation of the O-DCCAEP technique is carried out against an own dataset and the outcomes highlighted the betterment of the presented O-DCCAEP approach on existing approaches.

关键词： Churn prediction customer retention deep learning machine learning archimedes optimization algorithm

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A genetic algorithm-based solution for the problem of small disjuncts 4th

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4th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2000

作者： Carvalho, Deborah R. Freitas, Alex A. Postgraduate program in applied computer science R. Imaculada Conceicao 1155 CuritibaPR805215-901 Brazil Computer Science Dept. Av. Comendador Franco 186. CuritibaPR80215-090 Brazil

ISBN: (纸本)9783540410669

In essence, small disjuncts are rules covering a small number of examples. Hence, these rules are usually error-prone, which contributes to a decrease in predictive accuracy. The problem is particularly serious because, although each small disjuncts covers few examples, the set of small disjuncts can cover a large number of examples. This paper proposes a solution to the problem of discovering accurate small-disjunct rules based on genetic algorithms. The basic idea of our method is to use a hybrid decision tree/genetic algorithm approach for classification. More precisely, examples belonging to large disjuncts are classified by rules produced by a decision-tree algorithm, while examples belonging to small disjuncts are classified by a new genetic algorithm, particularly designed for discovering small-disjunct rules. © Springer-Verlag Berlin Heidelberg 2000.

关键词： Genetic algorithms

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Cuisine Image Recognition and Recommender System using Convolutional Neural Network 5

Cuisine Image Recognition and Recommender System using Convo...

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5th IEEE Eurasia Conference on IOT, Communication and Engineering, ECICE 2023

作者： Chang, Chin-Chih Wei, Chi-Hung Wu, Kuan-Yun Kao, Hao-Xiang Hsiao, Sean Chung Hua University Department of Computer Science and Information Engineering Hsinchu Taiwan Chung Hua University Ph.D. Program in Engineering Science Hsinchu Taiwan National Kaohsiung University of Science and Technology Department of Computer Science and Information Engineering Kaohsiung Taiwan Chung Hua University Program of Applied Foreign Language and Smart Commerce Hsinchu Taiwan

ISBN: (纸本)9798350314694

The fusion of technology and culinary exploration has allowed for the emergence of advanced online customer service systems. We developed a novel approach to enhance the dining experience. We used a Cuisine Image Recognition and Recommender System (CIRRS) powered by Convolutional Neural Network (CNN) to identify and suggest diverse cuisines based on visual inputs. CIRRS swiftly identified diverse cuisines from user-captured images, offering information on origin, ingredients, and variations by crawling websites. The system enhanced dining experiences by suggesting personalized menus based on individual preferences and past selections. Extensively tested across various culinary genres, CIRRS consistently demonstrated accuracy and adaptability. User feedback validated its potential to simplify dining choices and elevate satisfaction. This innovative system enriched dining experiences as a valuable tool for culinary enthusiasts, chefs, and restaurateurs, bridging the gap between technology and gastronomy, It also offers a unique way to explore Taiwanese cuisines. © 2023 IEEE.

关键词： convolutional neural network (CNN) deep learning image recognition recommender system web crawler

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Multiagent-based model integration

Multiagent-based model integration

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2006 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology

作者： De Paula, Ana Carolina M. Pilatti Ávila, Bráulio C. Scalabrin, Edson Enembreck, Fabrício Pontifical Catholic University of Paraná - PUCPR Graduate Program in Applied Computer Science - PPGIA Rua Imaculada Conceicao 1155 CEP 80.215-901 Curitiba PR Brazil

ISBN: (纸本)0769527493

This paper presents a Distributed Data Mining technique based on a multiagent environment, called SMAMDD (MultiAgent System for Distributed Data Mining), which uses model integration. Model Integration consists in the amalgamation of local models into a global, consistent one. In each subset, agents perform mining tasks locally and, afterwards, results are merged into a global model. In order to achieve that, agents cooperate by exchanging messages, aiming to improve the process of knowledge discover generating accurate results. The multiagent system for Distributed Data Mining proposed in this paper has been compared with classical machine learning algorithms which are based on model integration as well, simulating a distributed environment. The results obtained show that SMAMDD can produce highly accurate data models. © 2006 IEEE.

关键词： Multi agent systems

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Visualizing Field-free Deterministic Magnetic Switching of all–van der Waals Spin-Orbit Torque System Using Spin Ensembles in Hexagonal Boron Nitride

arXiv

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arXiv 2025年

作者： Zhang, Xi Zhou, Jingcheng Hu, Chaowei Deng, Kuangyin Wang, Chuangtang Agarwal, Nishkarsh Jin, Hanshang Al-Matouq, Faris A. Xu, Stelo Trivedi, Roshan S. Li, Senlei Rathi, Sumedh Lu, Hanyi Jiang, Zhigang Taufour, Valentin Hovden, Robert Zhao, Liuyan Cheng, Ran Xu, Xiaodong Chu, Jiun-Haw Du, Chunhui Rita Wang, Hailong School of Physics Georgia Institute of Technology AtlantaGA30332 United States Department of Physics University of Washington SeattleWA98105 United States Department of Electrical and Computer Engineering University of California RiversideCA92521 United States Department of Physics University of Michigan Ann ArborMI48109 United States Department of Materials Science and Engineering University of Michigan Ann ArborMI48109 United States Department of Physics and Astronomy University of California DavisCA95616 United States Department of Physics University of California San Diego La Jolla CA92093 United States Applied Physics Program University of Michigan Ann ArborMI48109 United States Department of Physics and Astronomy University of California RiversideCA92521 United States Department of Materials Science and Engineering University of Washington SeattleWA98105 United States

Recently, optically active spin defects embedded in van der Waals (vdW) crystals have emerged as a transformative quantum sensing platform to explore cutting-edge materials science and quantum physics. Taking advantage of excellent solid-state integrability, this new class of spin defects can be arranged in controllable nanoscale proximity of target materials in vdW heterostructures, showing great promise for improving spatial resolution and field sensitivity of current sensing technologies. Building on this state-of-the-art measurement platform, here we report hexagonal boron nitride-based quantum imaging of field-free deterministic magnetic switching of room-temperature two-dimensional magnet Fe3GaTe2 in an all-vdW spin-orbit torque (SOT) system. By visualizing SOT-driven variations of nanoscale Fe3GaTe2 magnetic stray field profile under different conditions, we have revealed how the observed magnetic switching evolves from deterministic to indeterministic behavior due to the interplay between out-of-plane spins, in-plane spins and Joule heating. This understanding, which is otherwise difficult to access by conventional transport measurements, offers valuable insights on material design, testing, and evaluation of next-generation vdW spintronic devices. Copyright © 2025, The Authors. All rights reserved.

关键词： Van der Waals forces

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Case-based cybersecurity incident resolution 31

Case-based cybersecurity incident resolution

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31st International Conference on Software Engineering and Knowledge Engineering, SEKE 2019

作者： Colome, Marcelo Nunes, Raul Ceretta De Lima Silva, Luis Alvaro Graduate Program in Computer Science - PPGCC Applied Computing Department Federal University of Santa Maria Av. Roraima Campus UFSM Camobi Santa Maria RS Brazil

ISBN: (纸本)1891706489

Intelligent computing techniques have a paramount importance to the treatment of cybersecurity incidents. In such Artificial Intelligence (AI) context, while most of the algorithms explored in the cybersecurity domain aim to present solutions to intrusion detection problems, these algorithms seldom approach the correction procedures that are explored in the resolution of cybersecurity incident problems that already took place. In practice, knowledge regarding cybersecurity resolution data and procedures is being under-used in the development of intelligent cybersecurity systems, sometimes even lost and not used at all. In this context, this work proposes to integrate Case-Based Reasoning techniques and IODEF standard in order to retain concrete problem-solving experiences of cybersecurity incident resolution to be reused in the resolution of new incidents. Experimental results so far obtained with a Case-based Cybersecurity Incident Resolution System (CbCSecIRS) implemented show that information security knowledge can be retained in a reusable memory, so improving the resolution of new cybersecurity problems. © 2019 Knowledge Systems Institute Graduate School. All rights reserved.

关键词： Intrusion detection

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Poultry raising light control system for laying hens and broilers 2

Poultry raising light control system for laying hens and bro...

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2nd International Conference on Cybernetics and Innovations, ICCI 2023

作者： Pinthong, Thidarat Ganokratanaa, Thittaporn Phetchaburi Rajabhat University Department. of Business Information Management Phetchaburi Thailand King Mongkut's University of Technology Thonburi Applied Computer Science Program Bangkok Thailand

ISBN: (纸本)9798350336573

Chicken is an economic animal. one kind At present, it has been raised as a business and has expanded extensively. This is because both domestic and foreign populations have a greater demand for products and processed products from laying hens. which the raising of laying hens must be more attention to the productivity and quality of eggs in order to meet the needs of consumers with high or low temperatures Too low has an effect on the physiological system of laying hens. Reduce egg production or may result in inefficient production. And with the aforementioned problems, technology has been used to help in notifying. Warn whether the temperature in the house is suitable to increase the production of high-quality eggs. © 2023 IEEE.

关键词： Internet of things

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Home smart alarm system for the visually impaired 2

Home smart alarm system for the visually impaired

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2nd International Conference on Cybernetics and Innovations, ICCI 2023

作者： Yimyam, Worawut Ganokratanaa, Thittaporn Phetchaburi Rajabhat University Department. of Business Information Management Phetchaburi Thailand King Mongkut's University of Technology Thonburi Applied Computer Science Program Bangkok Thailand

ISBN: (纸本)9798350336573

This research aims to study the working principles of IOT devices or Internet of Things in order to promote the use of information technology systems, both hardware and software, with visually impaired people. rehabilitation of persons with disabilities, enhancing the capacity or ability of persons with disabilities to improve their condition or or existing capabilities through the advancement of technology so that people with disabilities have the opportunity to work or live in society to the full potential of the researcher The concept of technology acceptance model (Technology Acceptance Model or TAM) to help further develop This research shows the importance of information technology systems, both hardware and software, to visually impaired people, which is the basis for product development of healthcare service businesses in the future. © 2023 IEEE.

关键词： Alarm systems

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Using asymmetric keys in a certified trust model for multiagent systems

Using asymmetric keys in a certified trust model for multiag...

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作者： Botêlho, Vanderson Enembreck, Fabrício Ávila, Bráulio De Azevedo, Hilton Scalabrin, Edson Graduate Program on Applied Computer Science Pontifical Catholic University of Paraná CEP: 80215-901 Curitiba Paraná Brazil Graduate Program on Technology Federal Technological University of Paraná CEP: 80.230-901 Curitiba Paraná Brazil

We present a contribution based on encryption to the model for the certification of trust in multiagent systems. The originality of the proposal remains in the use of asymmetric keys that allow the local storage of testimonies with the service agents that were assessed. The aim is to raise the level of efficiency that client agents have when contracting specialized service agents. To reach this objective we make three hypotheses: (i) client agents are able to measure and inform the quality of a service they receive from a service agent;(ii) distributed certificate control is possible if every service agent stores the certificates it receives from its client agents and, (iii) the content of a certificate can be considered safe as long as the public and private keys used to encrypt the certificate remain safe. This approach reduces some weak points of trust models that rely on the direct interaction between service and client agents (direct trust) or those that rely on testimony obtained from client agents (propagated trust). Simulation showed that encrypted certificates of trust improved the efficiency of client agents when choosing their service provider agents. The reason seems to be that the reputation of a given service provider agent is based on the reputation it has among the totality of client agents that used its services. © 2010 Elsevier Ltd. All rights reserved.

关键词： Multi agent systems

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Physics-informed neural networks for modeling water flows in a river channel

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第3期5卷 1001-1015页

作者： Nazari, Luis Fernando Camponogara, Eduardo Seman, Laio Oriel Department of Mathematics Federal Institute of Education Science and Technology Catarinense Rio do Sul89160-202 Brazil Department of Automation and Systems Engineering Federal University of Santa Catarina Florianopolis88040-900 Brazil Program in Applied Computer Science Universidade Do Vale Do Itajai Itajai88302-901 Brazil

The impacts incurred by floods regularly affect the planets population, inflicting social and economic problems. Optimal control strategies based on reservoir management may aid in controlling floods and mitigating the resulting damage. To this end, an accurate dynamic representation of water systems is needed. In practice, flood control strategies rely on hydrological forecasting models obtained fromconceptual or data-drivenmethods. Encouraged by recent works, this research proposes a novel surrogate model for water flow in a river channel based on physics-informed neural networks (PINNs). This approach achieved promising results regarding the assimilation of real-data measurements and the parameter identification of differential equations that govern the underlying dynamics. This article investigates PINN performance in a simulated environment built directly from a configuration of the Saint-Venant equations. The objective is to create a suitable model with high prediction accuracy and scientifically consistent behavior for use in real-Time applications. The experiments revealed promising results for hydrological modeling and presented alternatives to solve the main challenges found in conventional methods while assisting in synthesizing real-world representations. Impact Statement-The research seeks to contribute to the hydrological modeling area with a surrogate model based on physicsinformed neural networks (PINNs) to water flow in a watershed. In practice, thesemodels use conceptual or *** models to reach the precision provided by themethodology use large numbers of physical parameters. These parameters can demand deep knowledge about the environment and are possibly hard to identify in a complex basin. On the other hand, while data-driven methods do not require such knowledge about the dynamic system, they depend on a reliable and useful database to guarantee the accuracy of system *** introduce PINNs as a viable solution for

关键词： Floods

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