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Estimation of CS of the HPC with hybrid RBF neural networks

INTERNATIONAL JOURNAL OF KNOWLEDGE-BASED AND INTELLIGENT ENGINEERING SYSTEMS 2024年第2期29卷 188-201页

作者： Lu, Tao Wang, Yubian Ma, Chaohui She, Mingxing Liu, Min Dong, Fenghui Poly Changda Engn CO LTD Guangzhou Guangdong Peoples R China Kunming Univ Sci & Technol Kunming 650500 Yunnan Peoples R China Nanjing Forestry Univ Coll Civil Engn Nanjing Jiangsu Peoples R China China Railway Bridge & Tunnel Technol CO LTD Nanjing Jiangsu Peoples R China

This study used a radial function neural network (RBFNN) to create a novel system for calculating high-performance concrete's (HPC) compressive strength (CS) modified with fly ash and blast furnace slag. These admixtures could affect the mechanical and physical properties of HPC, and determining it definitely requires experimental efforts and costs. Herein, alternative methods such as machine learning algorithms named RBFNN could be useful to address these questions. The SSA (Salp swarm algorithm) and the artificial hummingbird algorithm (AHA) were utilized in this work to find optimal values of hyperparameters of the RBFNN approach that can be tuned. The suggested models were assessed utilizing a comprehensive dataset including 1030 data rows. Finally, the findings were compared to those documented in the literature. The findings of the calculations, which took into account evaluation metrics, depict that both hybrid SSA-RBFNN and AHA-RBFNN analysis might astonishingly perform good productivity during estimating, with R2 values of 0. 8955 and 0.8608 for SSA-RBFNN and 0.8987 and 0.8643 for AHA-RBFNN, respectively, related to the test and train segments. In conclusion, the AHA-RBFNN model created for predicting the CS of HPC amended with BFS and FA could be identified as the proposed model to be applied in practical applications.

关键词： CS high-performance concrete fly ash blast furnace slag RBF optimization algorithms

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Applications of Energy Storage Systems in Enhancing Energy Management and Access in Microgrids: A Review

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ENERGIES 2023年第16期16卷 5930页

作者： Ali, Ziad M. Calasan, Martin Aleem, Shady H. E. Abdel Jurado, Francisco Gandoman, Foad H. Prince Sattam Bin Abdulaziz Univ Coll Engn Elect Engn Dept Wadi Addawaser 11991 Saudi Arabia Univ Montenegro Fac Elect Engn Podgorica 81000 Montenegro Inst Aviat Engn & Technol Dept Elect Power & Machines Engn Giza 25152 Egypt Univ Jaen Dept Elect Engn Linares 23700 Spain Reliabil & Safety Tech Ctr RSTER B-1930 Zaventem Belgium

As the world's population continues to grow and the demand for energy increases, there is an urgent need for sustainable and efficient energy systems. Renewable energy sources, such as wind and solar power, have the potential to play a significant role in meeting this demand, but their intermittency can make integration into existing energy systems a challenge. Moreover, the development of sustainable energy systems has become even more critical in recent years, due to a confluence of events, including the decline in fuel prices, geopolitical conflicts, and the recent COVID-19 pandemic. The decrease in fuel prices has led to a decline in investment in renewable energy and has slowed the transition to sustainable energy systems. Additionally, geopolitical conflicts and pandemics have highlighted the need for resilient and self-sufficient energy systems that can operate independently of external factors. Also, energy storage technologies play a critical role in achieving this goal by providing reliable backup power and enabling microgrids to operate independently of the larger power grid. As such, developing efficient and effective energy storage technologies is essential for creating sustainable energy systems that can meet the demands of modern society while mitigating the impact of external factors. In this regard, this work provides an overview of microgrids' latest energy storage technologies, including their applications, types, integration strategies, optimization algorithms, software, and uncertainty analysis. Energy storage technologies have a wide range of applications in microgrids, including providing backup power and balancing the supply and demand of energy. Different energy storage techniques have been discussed, including batteries, flywheels, supercapacitors, pumped hydro energy storage, and others. Moreover, integration strategies of energy storage in microgrids, models, assessment indices, and optimization algorithms used in the design of energy sto

关键词： assessment indices batteries energy access energy storage energy management microgrids optimization algorithms power sharing software uncertainty analysis

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Integrating Design for Assembly Guidelines in Packaging Design with a Context-based Approach

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Procedia CIRP 2014年 21卷 342-347页

作者： P. Betancur-Muñoz G. Osorio-Gómez J.F. Martínez-Cadavid J.F. Duque-Lombana Design Engineering Research Group Universidad EAFIT Medellín Colombia Applied Mechanics Research Group Universidad EAFIT Medellín Colombia

In the product lifecycle, the packaging, as an object, has been on the back burner with respect to product and production systems design and some authors stated that its influence starts at the packing stage and ends when the customer obtains the product. Only a few years ago, its strategic role, protecting, containing and preserving the product, has been recognized, both in theory and in practice [1]. In this way, the packaging design has been focused in the accomplishment of some specific objectives, such as cost and space saving, material reduction, and quality problems avoidance. These approaches are object-related, but the design process is not considering that the packaging is also utilized to handle, transport, distribute, retail and promote the product. Therefore, even if mathematical solutions could be obtained for space optimization problems, these could not be relevant at industrial level since they are unfeasible throughout the packaging lifecycle, from either logistics or quality standpoints; and new restrictions should be considered. An approach proposed by Lee & Lye [2], called “Design for manual Packaging (DFPkg)”, is based on Design for the Environment (DFEnv) and Design for Assembly (DFA) guidelines, since the activities related with packaging could be considered as assembly activities seeing that all the packed pieces are part of a unique system. Nevertheless, some guidelines from DFA are omitted or decontextualized and they are not connected to restrictions in the mathematical models. This paper presents an integral approach for packaging design, complementing the guidelines proposed by Lee & Lye [2] in key contexts of the packaging lifecycle, in order to generate restrictions for an optimization model. Besides, this approach has been validated with a real industrial case study where the obtained solution is compared with the current one.

关键词： Packaging Design Design for Assembly optimization algorithms

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Démarche de prélocalisation des pertes physiques sur un réseau de distribution d'eau potable par l'optimisation du modèle hydraulique via un algorithme évolutionnaire

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LHB 2016年第6期102卷 59-66页

作者： Karima Sebbagh Abdelhamid Safri Moula Zabot Olivier Narbey Laboratoire Environnement Géotechnique et hydraulique (LEG-HYD)/Université des Sciences et de la Technologie - Houari Boumediene (USTHB) Algérie - Suez Environnement -

La gestion durable des réseaux de distribution d'eau potable est un enjeu majeur surtout pour les pays émergents où les rendements de réseau sont très faibles. La localisation et la priorisation des zones fuyardes deviennent une préoccupation majeure pour les services publics afin d'optimiser les ressources et d'améliorer la continuité de service. Les fuites dans les réseaux d'eau apparaissent généralement suite au vieillissement ou à une dégradation mécanique des *** le présent document, une approche d'aide à la décision sera proposée pour prélocaliser les zones à fort débit de fuites. Elle se base sur la résolution de l'équation de FAVAD (Fixed And Variable Area Discharge) en optimisant ses paramètres (coefficients et exposant de l'émetteur) via l'utilisation d'Algorithmes Génétiques (AG) couplés à une modélisation hydraulique interfacée avec un système d'information géographique (SIG).Deux outils ont été développés ; ExpaGIS et Optim_Detect pour résoudre respectivement les problématiques d'export des données et paramètres d'entrée du modèle hydraulique depuis le système d'information géographique ainsi que la répartition spatio-temporelle des pertes physiques dans un étage de *** démarche permet une interprétation en quasi-temps réel et automatisée des données de pression notamment, en les convertissant en une suspicion de fuites. L'exemple du réseau de Zeralda à Alger, d'un linéaire de 12 km est présenté pour démontrer l'efficacité de l'approche proposé*** Sustainable management of water distribution networks is a crucial challenge especially in emerging countries where distribution networks have a very low efficiency with very high levels of Non-Revenue Water. Locating and prioritizing of water leakage areas becomes a main concern for public services to optimize the use of resources and improve constancy of supply. Leaks in water systems generally appear due to the aging of the infrastructure, generated or amplified by corrosio

关键词： algorithmes d'optimisation fuites réseau de distribution FAVAD EPANET optimization algorithms leaks distribution network FAVAD EPANET

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A new quadratic programming strategy for efficient sparsity exploitation in SQP-based nonlinear MPC and MHE

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IFAC Proceedings Volumes 2014年第3期47卷 2945-2950页

作者： Janick V. Frasch Milan Vukov Hans Joachim Ferreau Moritz Diehl Department of Electrical Engineering KU Leuven Belgium Department of Mathematics Magdeburg University Germany ABB Corporate Research Baden-Dättwil Switzerland

A large class of algorithms for nonlinear model predictive control (MPC) and moving horizon estimation (MHE) is based on sequential quadratic programming and thus requires the solution of a sparse structured quadratic program (QP) at each sampling time. We propose a novel algorithm based on a dual two-level approach involving a nonsmooth version of Newton's method that aims at combining sparsity exploitation features of an interior point method with warm-starting capabilities of an active-set method. We address algorithmic details and present the open-source implementation qpDUNES. The effectiveness of the solver in combination with the ACADO Code Generation tool for nonlinear MPC is demonstrated based on set of benchmark problems, showing significant performance increases compared to the established condensing-based approach, particularly for problems with long prediction horizons.

关键词： Predictive Control optimization algorithms Open-Source Software

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Optimal task positioning in multi-robot cells, using nested meta-heuristic swarm algorithms

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Procedia CIRP 2018年 72卷 386-391页

作者： G. Nicola N. Pedrocchi S. Mutti P. Magnoni M. Beschi Consiglio Nazionale delle Ricerche Institute of Industrial Technologies and Automation via A. Corti 12 20133 Milan Italy

Process planning of multi-robot cells is usually a manual and time consuming activity, based on trials-and-errors. A co-manipulation problem is analysed, where one robot handles the work-piece and one robot performs a task on it and a method to find the optimal pose of the work-piece is proposed. The method, based on a combination of Whale optimization Algorithm and Ant Colony optimization algorithm, minimize a performance index while taking into account technological and kinematics constraints. The index evaluates process accuracy considering transmission elasticity, backslashes and distance from joint limits. Numerical simulations demonstrate the method robustness and convergence.

关键词： Task placement accuracy indexes optimization algorithms industrial robotics

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3I Buildings: Intelligent, Interactive and Immersive Buildings

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Procedia Engineering 2015年 123卷 7-14页

作者： António Aguiar Costa Pedro Mira Lopes André Antunes Izunildo Cabral António Grilo Filipe Martins Rodrigues CERIS Instituto Superior Técnico Universidade de Lisboa Portugal Unidemi Faculdade de Ciências e Tecnologia Universida Nova de Lisboa Portugal Siemens Lisboa Portugal

This research presents the architecture of a technology platform capable of integrating different types of data from building sensors and providing an interface to manage and operate facility devices, which is supported by advanced optimization algorithms. This interface is potentiated by a BIM-based interface presenting real-time data of the building. The solution, called 3i buildings - Intelligent, Interactive, and Immersive Buildings, is a tool to monitor and manage smart buildings, as well as optimize users experience, energy consumptions and environment quality. This is achieved by a grid of sensors and devices that continuously gather information (structural conditions of the building, occupancy, comfort of occupants, energy consumptions and CO2, COV's and Humidity levels, etc.), which is processed by predictive models able to learn over time. The 3D representation of the models allows managers to take advantage of the virtual environment, by augmenting the facility model and including information about the facility, making it easier and perceptible to users and owners, helping them to make better decisions. To support our research, the system will be installed in three different environments, Luz's hospital, Lisbon Aquarium and Norte Shopping, to test the solution under different conditions, objectives and users. In the first two cases the objectives are to monitor building air quality, consumptions and occupancy and in the Norte Shopping case the objectives are to monitor people flows, interact with tem and help the response in case of crisis according to the adopted emergency plan. These types of systems might help reducing energy consumptions as well as increasing comfort and satisfaction of occupants, maintaining a constant concentration of CO2 and humidity within the facility. The optimized algorithms will allow the system to learn, predicting and reacting to different conditions, giving a more reliable and smooth response to occupants needs.

关键词： Intelligent Buildings Energy Efficiency optimization algorithms BIM IFC

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A model predictive control application for air quality management

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IFAC-PapersOnLine 2024年第18期58卷 244-249页

作者： L. Sangiorgi C. Carnevale S. De Nardi S. Raccagni

This study introduces a model predictive control methodology to determine optimal measures for mitigating air pollution, assisting Local Authorities in policy development. Anchored in an auto-regressive model, it analyzes dynamic air quality patterns over a defined timeframe using daily observed pollutant concentration, meteorological variables, and estimated emission data. Employing model predictive control methodology, the approach aims to optimize daily emission reductions. Evaluated in Milan, a heavily polluted European city, the findings highlight the methodology's potential as a robust tool for Local Authorities, enabling informed decisions in crafting efficient air quality management strategies, in the specific context of NO 2 .

关键词： Control application Model Predictive Control optimization algorithms Complex systems Modelling Simulation

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Evolving Convolutional Neural Networks with Meta-Heuristics for Transfer Learning in Computer Vision

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Procedia Computer Science 2023年 230卷 658-668页

作者： V Srilakshmi G Uday Kiran M Mounika A Sravanthi N V K Sravya V N S Akhil M Manasa

In the rapidly evolving landscape of computer vision and artificial intelligence, transfer learning has emerged as a powerful tool for efficiently applying pre-trained models to new tasks. This article delves into the intriguing concept of evolving Convolutional Neural Networks (CNNs) with meta-heuristics for transfer learning in computer vision. The primary focus is on enhancing the adaptability and efficiency of CNNs, making them better suited for specialized tasks. The article covers the significance of transfer learning, the challenges faced in transfer learning with CNNs, the basics of CNN architecture, and the role of meta-heuristics in optimizing CNNs. Real-world applications and success stories demonstrate the transformative potential of these techniques in fields like medical image analysis and autonomous vehicles. It explores emerging trends and potential developments in the domain, emphasizing the impact on various sectors, including healthcare, natural language processing, and robotics. The promise of evolving CNNs with meta-heuristics lies in their capacity to tackle intricate problems with greater precision, ultimately reshaping the landscape of artificial intelligence and machine learning. Ongoing research ensures a promising future for this amalgamation of technologies, promising breakthroughs that will have a lasting impact on the world of computer vision and beyond.

关键词： Convolution Neural Network (CNN) Transfer Learning Meta-Heuristics Computer Vision optimization algorithms

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Adaptive actor-critic structure for parametrized controllers

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IFAC-PapersOnLine 2019年第16期52卷 652-657页

作者： Thomas Göhrt Pavel Osinenko Stefan Streif Technische Universität Chemnitz Germany

Given a parametrized stabilizing controller, the approach presented in this work seeks to find optimal parameters with respect to an infinite-horizon cost. Since the latter is in general not computable, it is suggested to apply an adaptive actor-critic structure to approximate the respective value function. The actor is realized explicitly using the projected subgradient method. A particular challenge arises from the fact that the approximated value function is time-varying depending on the evolution of the dynamical system and critic’s approximation of the value function. Provided that a certain stability constraint is convex and under persistence of excitation conditions, it is shown that the actor and critic parameters converge to prescribed vicinities of the optimal values. The whole setup is done in continuous time. A computational study is presented.

关键词： Nonlinear control adaptive control optimal control optimization algorithms

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