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A multi-objective optimization of a building's total heating and cooling loads and total costs in various climatic situations using response surface methodology

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ENERGY REPORTS 2021年 7卷 7520-7538页

作者： Baghoolizadeh, Mohammadreza Rostamzadeh-Renani, Reza Rostamzadeh-Renani, Mohammad Toghraie, Davood Univ Shahreza Fac Engn Dept Mech Engn Shahreza *** Iran Islamic Azad Univ Dept Mech Engn Khomeinishahr Branch Khomeinishahr Iran

Excessive rise in energy consumption has been one of the major predicaments of recent decades. Among all the sectors, residential buildings are one of the main consumers of energy resources. Because air conditioning systems are the main ground for using energy inside houses, researchers have proposed diverse methods of reducing energy loss such as encapsulating insulators in wall structures. In this paper, the main focus is to calculate and then optimize the total heating and cooling loads as well as the total costs. The building model was simulated in cities with different climatic situations using EnergyPlus software. For optimization, five design variables were determined and 300 Design of Experiment points were considered for each city to measure the objective Functions, which are the building's total load and cost. To find the optimal states, Response Surface Methodology (RSM) is utilized to predict continuous functions from discrete data of experiments. Consequently, total load and total costs of building in various climatic conditions were improved by a range of 2%-16%, and the Static Payback Period and Human Heating Comfort were ameliorated dramatically. (C) 2021 The Authors. Published by Elsevier Ltd.

关键词： Cooling set point temperature Insulator Heating set point temperature multi-objective-optimization Response surface methodology Total heating and cooling loads Total costs

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multi objective optimization of classification rules using Cultural Algorithms

Multi Objective Optimization of classification rules using C...

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International Conference on Communication Technology and System Design

作者： Srinivasan, Sujatha Ramakrishnan, Sivakumar AVVM Sri Pushpam Coll Dept Comp Sci Tanjore 613503 Tamil Nadu India

Classification rule mining is the most sought out by users since they represent highly comprehensible form of knowledge. The rules are evaluated based on objective and subjective metrics. The user must be able to specify the properties of the rules. The rules discovered must have some of these properties to render them useful. These properties may be conflicting. Hence discovery of rules with specific properties is a multi objective optimization problem. Cultural Algorithm (CA) which derives from social structures, and which incorporates evolutionary systems and agents, and uses five knowledge sources (KS's) for the evolution process better suits the need for solving multi objective optimization problem. In the current study a cultural algorithm for classification rule mining is proposed for multi objective optimization of rules. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of ICCTSD 2011

关键词： multi-objective-optimization Classification Cultural Algorithm Data mining

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Adaptability-Driven multi-objective Hardware optimization for Vehicular Systems 100

Adaptability-Driven Multi-Objective Hardware Optimization fo...

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100th IEEE Vehicular Technology Conference, VTC 2024-Fall

作者： Demicoli, Julian Steinhorst, Sebastian Technical University of Munich Munich Germany

ISBN: (纸本)9798331517786

Vehicular systems operate under diverse and often unpredictable operating conditions, necessitating robust adaptability to manage these uncertainties effectively. Traditionally, adaptability is linked to software capabilities, with hardware platforms frequently overlooked as variables for enhancement. This paper introduces a novel optimization framework aimed at improving the adaptability of vehicular systems during the hardware design phase. We develop an Adaptability Score and integrate it into a multi-objective optimization (MOO) framework, presenting its mathematical formulation and its application in hardware optimization. The efficacy of this framework is evaluated through its application to a real-world Hyperloop magnetic levitation system. Our results demonstrate that, compared to a baseline hardware configuration optimized without considering the Adaptability Score, our approach maintains multi-objective system performance across various anomalous scenarios by enhancing the system's capability to adapt through improved hardware-software synergy. © 2024 IEEE.

关键词： Adaptation Design Automation Hardware optimization multi-objective-optimization Resilience

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A hybrid green energy-based system with a multi-objective optimization approach for optimal frost prevention in horticulture

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JOURNAL OF CLEANER PRODUCTION 2021年 329卷 129563-129563页

作者： Atam, Ercan Abdelmaguid, Tamer F. Keskin, Muhammed Emre Kerrigan, Eric C. Imperial Coll London Dept Elect & Elect Engn London England Cairo Univ Dept Mech Design & Prod Giza Egypt Ataturk Univ Dept Ind Engn Erzurum Turkey

Frost affects horticultural plants considerably and result in multi-dimensional harms: from economic losses to psychological problems for people involved in horticulture. As a result, prevention of frost in horticulture is of utter most importance for many countries. In this paper, first we propose a novel green energy-integrated solution, a hybrid renewable energy-based system involving active heaters, for this less studied, but very important problem. We then develop a multi-objective robust optimization-based formulation for optimization of the proposed system in order to (i) optimize the distribution of a given number of active heaters in a given large-scale orchard to optimally heat the orchard by the proposed frost prevention system and (ii) optimize the layout of the thermal energy distribution network to minimize the total pipe length (which is directly related to the installation cost and the cost of energy losses during energy transfer). Finally, the resulting optimization problem is approximated using a discretization scheme. A case study is provided to give an idea of the potential savings using the proposed optimization method compared to the result from a heuristic-based design, which showed a 24.13% reduction in the total pipe length and a 54.29% increase in optimal heating. Compared to current active frost prevention methods, the proposed hybrid green energy system for frost protection is a cleaner, environmentally friendly and potentially cost-effective solution.

关键词： Hybrid energy systems Active horticulture frost prevention systems Optimal design multi-objective-optimization k-MST Robust optimization

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multi objective optimization of classification rules using Cultural Algorithms

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Procedia Engineering 2012年 30卷 457-465页

作者： Sujatha Srinivasan Sivakumar Ramakrishnan Department of Computer Science AVVM Sri Pushpam College Poondi Tanjore-613503 Tamil Nadu India

关键词： multi-objective-optimization Classification Cultural Algorithm Data mining

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Integration of natural and social environment in the implementation of geothermal projects

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GEOTHERMICS 2018年 73卷 111-123页

作者： Yasukawa, Kasumi Kubota, Hiromi Soma, Nobukazu Noda, Tetsuro Natl Inst Adv Ind Sci & Technol Renewable Energy Res Ctr 2-2-9 Machiikedai Koriyama Fukushima 9630298 Japan Cent Res Inst Elect Power Ind Tokyo Japan Natl Inst Adv Ind Sci & Technol Koriyama Fukushima Japan

Recent geoscientific, socio-technical, and sociological studies aimed at achieving social acceptance for geothermal development accommodating the natural and social environment are integrated in this paper. The geoscientific study presents the potential effects of geothermal development on the nearby hydraulic systems. Geochemical analysis of hot springs provides an effective means of investigating possible interference of the hot springs due to geothermal exploitation. The authors have proposed a socio-technical approach, Overall System Design, which is a concept aimed at maximizing business profitability and social acceptance. In this approach, the optimal solution may vary with the extent of project implementation because increasing data volume facilitates more accurate system design. Visualization of the benefits of geothermal development is an important part of this approach because it promotes mutual understanding among stakeholders. Stakeholder attitudes and needs are diverse hence from a sociological approach, project developers approach for social acceptance should differ depending on the situation for each geothermal prospect. Results of attitude surveys of local municipal governments as key stakeholders suggest that governments and developers should continue to provide information to improve social acceptance. In order to achieve social acceptance, explanation based on geoscientific facts and the concept of Overall System Design may be effective.

关键词： Integrated assessment Social acceptance Environmental Technical Geochemistry Hydraulic connection Overall system design (OSD) multi-objective-optimization Stakeholder analysis

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Novel system identification method and multi-objective-optimal multivariable disturbance observer for electric wheelchair

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ISA TRANSACTIONS 2013年第1期52卷 129-139页

作者： Saadatzi, Mohammad Nasser Poshtan, Javad Saadatzi, Mohammad Sadegh Tafazzoli, Faezeh Iran Univ Sci & Technol Tehran Iran Multimedia Univ Melaka Malaysia Polytech Univ Technol Tehran Iran

Electric wheelchair (EW) is subject to diverse types of terrains and slopes, but also to occupants of various weights, which causes the EW to suffer from highly perturbed dynamics. A precise multivariable dynamics of the EW is obtained using Lagrange equations of motion which models effects of slopes as output-additive disturbances. A static pre-compensator is analytically devised which considerably decouples the EW's dynamics and also brings about a more accurate identification of the EW. The controller is designed with a disturbance-observer (DOB) two-degree-of-freedom architecture, which reduces sensitivity to the model uncertainties while enhancing rejection of the disturbances. Upon disturbance rejection, noise reduction, and robust stability of the control system, three fitness functions are presented by which the DOB is tuned using a multi-objective optimization (MOO) approach namely non-dominated sorting genetic algorithm-II (NSGA-II). Finally, experimental results show desirable performance and robust stability of the proposed algorithm. (C) 2012 ISA. Published by Elsevier Ltd. All rights reserved.

关键词： Electric wheelchair Dynamic modeling System identification Robust disturbance observer Characteristic loci method Non-dominated sorting genetic algorithm II multi-objective-optimization

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Fine-Grained Power Modeling of multicore Processors Using FFNNs

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INTERNATIONAL JOURNAL OF PARALLEL PROGRAMMING 2022年第2期50卷 243-266页

作者： Sagi, Mark Nguyen Anh Vu Doan Fasfous, Nael Wild, Thomas Herkersdorf, Andreas Tech Univ Munich Munich Germany

To minimize power consumption while maximizing performance, today's multicore processors rely on fine-grained run-time dynamic power information-both in the time domain, e.g. mu s to ms, and space domain, e.g. core-level. The state-of-the-art for deriving such power information is mainly based on predetermined power models which use linear modeling techniques to determine the core-performance/core-power relationship. However, with multicore processors becoming ever more complex, linear modeling techniques cannot capture all possible core-performance related power states anymore. Although artificial neural networks (ANN) have been proposed for coarse-grained power modeling of servers with time resolutions in the range of seconds, few works have yet investigated fine-grained ANN-based power modeling. In this paper, we explore feed-forward neural networks (FFNNs) for core-level power modeling with estimation rates in the range of 10 kHz. To achieve a high estimation accuracy while minimizing run-time overhead, we propose a multi-objective-optimization of the neural architecture using NSGA-II with the FFNNs being trained on performance counter and power data from a complex-out-of-order processor architecture. We show that relative power estimation error for the highest accuracy FFNN decreases on average by 7.5% compared to a state-of-the-art linear power modeling approach and decreases by 5.5% compared to a multivariate polynomial regression model. For the FFNNs optimized for both accuracy and overhead, the average error decreases between 4.1% and 6.7% compared to linear modeling while offering significantly lower overhead compared to the highest accuracy FFNN. Furthermore, we propose a micro-controller-based and an accelerator-based implementation for run-time inference of the power modeling FFNN and show that the area overhead is negligible.

关键词： Processor multicore Power Modeling Estimation Core-level Artificial neural network ANN FFNN Accuracy Error Overhead multi-objective-optimization NSGA-II

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Shark

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JOURNAL OF MACHINE LEARNING RESEARCH 2008年第6期9卷 993-996页

作者： Igel, Christian Heidrich-Meisner, Verena Glasmachers, Tobias Ruhr Univ Bochum Inst Neuroinformat D-44780 Bochum Germany

SHARK is an object-oriented library for the design of adaptive systems. It comprises methods for single-and multi-objective optimization (e. g., evolutionary and gradient-based algorithms) as well as kernel-based meth... 详细信息

关键词： machine learning software neural networks kernel-methods evolutionary algorithms optimization multi-objective-optimization

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Joint Security-vs-QoS Framework: Optimizing the Selection of Intrusion Detection Mechanisms in 5G networks 22

Joint Security-vs-QoS Framework: Optimizing the Selection of...

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17th International Conference on Availability, Reliability and Security (ARES)

作者： Bozorgchenani, Arash Zarakovitis, Charilaos C. Chien, Su Fong Lim, Heng Siong Ni, Qiang Gouglidis, Antonios Mallouli, Wissam Univ Lancaster Lancaster England Natl Ctr Sci Res Demokritos Athens Greece MIMOS Berhad Kuala Lumpur Malaysia Multimedia Univ Cyberjaya Malaysia Montimage EURL Paris France

ISBN: (纸本)9781450396707

The advent of 5G technology introduces new - and potentially undiscovered - cybersecurity challenges, with unforeseen impacts on our economy, society, and environment. Interestingly, Intrusion Detection Mechanisms (IDMs) can provide the necessary network monitoring to ensure - to a big extent - the detection of 5G-related cyberattacks. Yet, how to realize the attack surface of 5G networks with respect to the detected risks, and, consequently, how to optimize the cybersecurity levels of the network, remains an open critical challenge. In respect, this work focuses on deploying multiple distributed Security Agents (SAs) that can run different IDMs over various network components and proposes a cybersecurity mechanism for optimizing the network's attack surface with respect to the Quality of Service (QoS). The proposed approach relies on a new closed-form utility function to describe the trade-off between cybersecurity and QoS and uses multi-objective optimization to improve the selection of each SA detection level. We demonstrate via simulations that before optimization, an increase in the detection level of SAs brings a direct decrease in QoS as more computational, bandwidth and monetary resources are utilized for IDM processing. Thereby, after optimization, we demonstrate that our mechanism can strike a balance between cybersecurity and QoS while show-casing the impact of the importance of different objectives of the joint optimization.

关键词： 5G cybersecurity system cost QoS multi-objective-optimization risk detection risk mitigation

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