Multiobjective Long-Term Generation Scheduling of Cascade Hydroelectricity System Using a Quantum-Behaved Particle Swarm Optimization Based on Decomposition

Hu, Hu; Yang, Kun

doi:10.1109/access.2020.2997864

Cited by 6 publications

(2 citation statements)

References 59 publications

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“…Finally, the improved optimal weights and thresholds of quantum particle swarms are used. The experimental results show that the improved quantum particle swarm optimization algorithm can effectively improve the global optimization ability and convergence of the traditional particle swarm, and make accurate predictions for this research [19][20][21].…”

Section: Figure 1: Improved Qpso Algorithm Flowchartmentioning

confidence: 91%

Utilizing the Improved QPSO Algorithm to Build a WSN Monitoring System

Sung¹,

Hsiao²

2022

Computers, Materials &Amp; Continua

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This research uses the improved Quantum Particle Swarm Optimization (QPSO) algorithm to build an Internet of Things (IoT) life comfort monitoring system based on wireless sensing networks. The purpose is to improve the quality of intelligent life. The functions of the system include automatic basketball court lighting system, monitoring of infants' sleeping posture and accidental falls of the elderly, human thermal comfort measurement and other related life comfort services, etc. On the hardware system of the IoT, this research is based on the latest version of ZigBee 3.0, which uses optical sensors, 3-axis accelerometers, and temperature/humidity sensors in the IoT perception layer. In the network transmission layer, the central network architecture is used for connection. In the application layer, we have designed a graphical interface for real-time values and information that can be read at any time and place using mobile devices. In this study, authors use the improved QPSO algorithm in the calculation part, so that the target can be effectively positioned outside the numerous surveillance data. This study uses various sensor data fusion technologies to make the IoT system becomes able to provide more extensive and even better services than ever before. In short, this research work has proven to be an effective way to reduce power consumption, improve medical quality and provide higher comfort for intelligent lift level.

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Section: Figure 1: Improved Qpso Algorithm Flowchartmentioning

confidence: 91%

Utilizing the Improved QPSO Algorithm to Build a WSN Monitoring System

Sung¹,

Hsiao²

2022

Computers, Materials &Amp; Continua

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“…Southwestern China [285] Develop a multi-objective quantum-behaved particle swarm optimization model based on improved Tchebycheff decomposition with a modified generator of direction vectors to maximize the total production rate and firm the hydropower output.…”

Section: Ref Main Goalmentioning

confidence: 99%

Dam System and Reservoir Operational Safety: A Meta-Research

Badr,

Li,

El-Dakhakhni

2023

Water

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Dams are critical infrastructure necessary for water security, agriculture, flood risk management, river navigation, and clean energy generation. However, these multiple, and often conflicting, objectives introduce complexity in managing dam operations. In addition, dam infrastructure has been evolving as complex systems-of-systems with multiple interacting components and subsystems, all susceptible to a wide range of uncertainties. Such complexities and uncertainties have triggered extensive research initiatives focused on dam systems and reservoir operational safety. Focusing on the latter, this paper meta-researches (conducts research-on-research) previously published studies to identify the critical research gaps and propose future research directions. In this respect, this paper first performs a quantitative analysis of the pertinent literature, using text mining and subsequent topic modeling, to identify and classify major and uncover latent topics in the field. Subsequently, qualitative analysis is conducted to critically review the identified topics, exploring the concepts, definitions, modeling tools, and major research trends. Specifically, the study identified seven topics: optimization models; climate change; flood risk; inflow forecasting; hydropower generation; water supply management; and risk-based assessment and management. The study also presents three main research gaps associated with the limitations in modeling concepts, modeling tools capabilities, and the lack of resilience-guided management of dam operational safety. Overall, this study presents a road map of the currently available dam and reservoir operational safety research and associated knowledge gaps, as well as potential future research directions to ensure the resilience of such critically important infrastructure, especially in the age of climate change.

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A brief review on quantum computing based drug design

Das,

Ray,

Bhattacharyya

et al. 2024

WIREs Data Min & Knowl

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Design and development of new drug molecules are essential for the survival of human society. New drugs are designed for therapeutic purposes to combat new diseases. Besides treating new diseases, new drug development is also needed to treat pre‐existing diseases more effectively and reduce the existing drugs' side effects. The design of drugs involves several steps, from the discovery of the drug molecule to its commercialization in the market. One of the most critical steps in drug design is to find the molecular interactions between the target (infected) molecule and the drug molecule. Several complex chemical equations need to be solved to determine the molecular interactions. In the late 20th Century, the advancement of computational technologies has made the solution of chemical equations relatively easier and faster. Moreover, the design of drug molecules involves multi‐criteria optimization. Classical computational methodologies have been used for drug design since the end of the 20th Century. However, nowadays, more advanced computational methodologies are inevitable in designing drugs for new diseases and drugs with fewer side effects. In this context, the quantum computing paradigm has proved beneficial in drug design due to its advanced computational capabilities. This paper presents a state‐of‐the‐art comprehensive review of the quantum computing‐based methodologies involved in drug design. A comparative study is made about the different quantum‐aided drug design methods, stating each methodology's merits and demerits. The review work presented in this manuscript will help new researchers assess the present state‐of‐the‐art concept of quantum‐based drug design.This article is categorized under: Technologies > Structure Discovery and Clustering Technologies > Computational Intelligence Application Areas > Health Care

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Multiobjective Long-Term Generation Scheduling of Cascade Hydroelectricity System Using a Quantum-Behaved Particle Swarm Optimization Based on Decomposition

Cited by 6 publications

References 59 publications

Utilizing the Improved QPSO Algorithm to Build a WSN Monitoring System

Utilizing the Improved QPSO Algorithm to Build a WSN Monitoring System

Dam System and Reservoir Operational Safety: A Meta-Research

A brief review on quantum computing based drug design

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