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Relevant bibliographies by topics / Experience-Driven Optimization

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Journal articles

Academic literature on the topic 'Experience-Driven Optimization'

Author: Grafiati

Published: 14 October 2023

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Journal articles on the topic "Experience-Driven Optimization"

1

Cheng, Yihua, Xu Zhang, and Junchen Jiang. "Enabling Perception-Driven Optimization in Networking." ACM SIGMETRICS Performance Evaluation Review 51, no. 2 (2023): 103–5. http://dx.doi.org/10.1145/3626570.3626608.

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Service providers struggle to catch up with the rapid growth in bandwidth and latency demand of Internet videos and other applications. An essential contributor to this resource contention is the assumption that users are equally sensitive to service quality everywhere, so any low-quality incidents must be avoided. However, this assumption is not true. For example, our work and other parallel efforts have shown that more video users can be served with better quality of experience (QoE) if we embrace the fact that the QoE's sensitivity to video quality varies greatly with the video content. To

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2

P, Dr Periasamy, and Dr Dinesh N. "Data Driven Marketing Strategic Trends in 2022." International Journal of Science, Engineering and Management 9, no. 6 (2022): 24–27. http://dx.doi.org/10.36647/ijsem/09.06.a005.

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This paper is an attempt to find out the significant data driven marketing strategic trends. The author has developed a model which will help the readers to under the data driven marketing strategies in the recents trends in the world very easily. This model is called EPCMASQ , a model of the author, That is Ethical Information, Personalized Marketing Automation, Better Customer Experience, Multi-channel Experience, Artificial Intelligence, Search Engine Optimization and Qualitative Data. With which the concept of data driven marketing strategies explained well.

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3

Shailesh, K. S., and P. V. Suresh. "Performance Driven Development Framework for Web Applications." Global Journal of Enterprise Information System 9, no. 1 (2017): 75. http://dx.doi.org/10.18311/gjeis/2017/15870.

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The performance of web applications is of paramount importance as it can impact end-user experience and the business revenue. Web Performance Optimization (WPO) deals with front-end performance engineering. Web performance would impact customer loyalty, SEO, web search ranking, SEO, site traffic, repeat visitors and overall online revenue. In this paper we have conducted the survey of state of the art tools, techniques, methodologies of various aspects of web performance optimization. We have identified key web performance patterns and proposed novel web performance driven development framewor

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4

SONG, WEI, DIAN TJONDRONEGORO, and MICHAEL DOCHERTY. "EXPLORATION AND OPTIMIZATION OF USER EXPERIENCE IN VIEWING VIDEOS ON A MOBILE PHONE." International Journal of Software Engineering and Knowledge Engineering 20, no. 08 (2010): 1045–75. http://dx.doi.org/10.1142/s0218194010005067.

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Compared with viewing videos on PCs or TVs, mobile users have different experiences in viewing videos on a mobile phone due to different device features such as screen size and distinct usage contexts. To understand how mobile user's viewing experience is impacted, we conducted a field user study with 42 participants in two typical usage contexts using a custom-designed iPhone application. With user's acceptance of mobile video quality as the index, the study addresses four influence aspects of user experiences, including context, content type, encoding parameters and user profiles. Accompanyi

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5

Wu, Xiaojing, Zijun Zuo, and Long Ma. "Aerodynamic Data-Driven Surrogate-Assisted Teaching-Learning-Based Optimization (TLBO) Framework for Constrained Transonic Airfoil and Wing Shape Designs." Aerospace 9, no. 10 (2022): 610. http://dx.doi.org/10.3390/aerospace9100610.

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The surrogate-assisted optimization (SAO) process can utilize the knowledge contained in the surrogate model to accelerate the aerodynamic optimization process. The use of this knowledge can be regarded as the primary form of intelligent optimization design. However, there are still some difficulties in improving intelligent design levels, such as the insufficient utilization of optimization process data and optimization parameters’ adjustment that depends on the designer’s intervention and experience. To solve the above problems, a novel aerodynamic data-driven surrogate-assisted teaching-lea

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6

Pairet, Eric, Constantinos Chamzas, Yvan R. Petillot, and Lydia Kavraki. "Path Planning for Manipulation Using Experience-Driven Random Trees." IEEE Robotics and Automation Letters 6, no. 2 (2021): 3295–302. http://dx.doi.org/10.1109/lra.2021.3063063.

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7

Endress, Felix, Jasper Rieser, and Markus Zimmermann. "ON THE TREATMENT OF REQUIREMENTS IN DFAM: THREE INDUSTRIAL USE CASES." Proceedings of the Design Society 3 (June 19, 2023): 2815–24. http://dx.doi.org/10.1017/pds.2023.282.

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AbstractOptimization-driven design offers advantages over traditional experience-based mechanical design. As an example, topology optimization can be a powerful tool to generate body shapes for Additive Manufacturing (AM). This is helpful, when (1) load paths are non-intuitive due to complex design domains or boundary conditions, or (2) the design process is to be automated to minimize effort associated with experience-based design. However, practically relevant boundary conditions are often difficult to put into a formal mathematical language to, for example, either feed it into a topology op

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8

Borba Evangelista, Gustavo, Guilherme Conceição Rocha, and Wlamir Olivares Loesch Vianna. "Aircraft Troubleshooting Optimization Using Case-based Reasoning and Decision Analysis." Annual Conference of the PHM Society 12, no. 1 (2020): 8. http://dx.doi.org/10.36001/phmconf.2020.v12i1.1170.

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   The Fault Isolation Manual (FIM) can be seen as a specialist system that carries the expectations and expertise of engineers and technical team concerning the aircraft components and systems operation. It is basically a manual that supports the maintainers regarding the actions to perform in determined situations to properly isolate a fault. Although the FIM is the most common tool that assists maintainer on the troubleshooting process today, it does not adequately consider field experience and it does not explore situations where the maintenance operator has limited resou

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9

Na, Chongzheng, and Huixin Liu. "A Historical Experience Surrogate Model Assisted Particle Swarm Optimization for Expensive Black-box Problems." Highlights in Science, Engineering and Technology 7 (August 3, 2022): 83–88. http://dx.doi.org/10.54097/hset.v7i.1021.

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This paper proposed a new historical experience surrogate model assisted particle swarm optimization method. This method extends the particle swarm optimization by adding new surrogate-based phase. In the classic phase, the particle swarm optimization runs the same way as the original algorithm, and the real function value evaluated are collected into the global database. In the surrogate phase, sub-swarms are generated following the distribution of the history data and evaluated by the surrogate model(s). The purpose of the surrogate phase is to explore the possible better solutions of the se

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10

Enríquez-Urbano, Juana, Marco Antonio Cruz-Chávez, Rafael Rivera-López, Martín H. Cruz-Rosales, Yainier Labrada-Nueva, and Marta Lilia Eraña-Díaz. "Metaheuristic to Optimize Computational Convergence in Convection-Diffusion and Driven-Cavity Problems." Mathematics 9, no. 7 (2021): 748. http://dx.doi.org/10.3390/math9070748.

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This work presents an optimization proposal to better the computational convergence time in convection-diffusion and driven-cavity problems by applying a simulated annealing (SA) metaheuristic, obtaining optimal values in relaxation factors (RF) that optimize the problem convergence during its numerical execution. These relaxation factors are tested in numerical models to accelerate their computational convergence in a shorter time. The experimental results show that the relaxation factors obtained by the SA algorithm improve the computational time of the problem convergence regardless of user

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