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Quantum Particle Swarm With Teamwork Evolutionary Strategy for Multi-Objective Optimization on Electro-Optical Platform
摘要： This paper deals with multi-objective optimization design of the airborne electro-optical platform to reduce its mechanical resonance, improve its stability, and reduce its mass. The traditional group intelligent algorithm could be easily fall into local optimum. This greatly affects its search accuracy; the multi-objective optimization of the optoelectronic platform cannot meet the design requirements with traditional algorithms. This paper proposes a teamwork evolutionary strategy quantum particle swarm optimization algorithm (TEQPSO) for balancing global and local search. This algorithm is based on a novel learning strategy consisting of cross-sequential quadratic programming and Gaussian chaotic mutation operators. The former performs the local search on the sample and the interlaced operation on the parent individual while the descendants of the latter generated by Gaussian chaotic mutation may produce new regions in the search space. Experiments performed on multimodal test and composite functions with or without coordinate rotation demonstrated that the population information could be utilized by the TEQPSO algorithm more effectively compared with the twelve QSOs and PSOs variants. This improves the algorithm performance, significantly. Finally, the TEQPSO algorithm is employed for multi-objective optimization design of the airborne electro-optical platform. This leads to significant vibration response and mass reduction as well as stiffness characteristics improvement. Finally, higher search accuracy and superior performance are obtained with the TEQPSO algorithm compared with the QPSO algorithm.
关键词： Multi-objective optimization,Quantum particle swarm,Teamwork evolutionary strategy,Electro-optical platform
更新于2025-09-11 14:15:04
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Feasibility of Photovoltaic Solar System for Rural Electrification
摘要： Growth of our nation will totally depend upon rural development. Rural development is the main concern of growth of farmers. Farmers total growth depends upon their basic root cause of traditional farming to mould into advanced farming. Rural development of farmers through awareness of advantages of economical, clean, environment friendly, pollution free, of available renewable energy sources PV based rural electrification system for advanced farming. Rural electrification is an integral component of poverty alleviation and nation growth. Government of India has a target of solar rural electrification for irrigation through solar pumps, solar tractors, solar advanced farming equipments. Here, this research is helpful for finding out difficulties in rural electrification, awareness of policies, fundings, loan facilities, subsidies and training for the farmers. Also this research indentifies what Steps are to be initiated with Rural Electric corporation, power sector reforms and State Electricity boards. Also this research provides the features of rural electrification in India and the photovoltaic solar farming, solar home systems for rural electrification.
关键词： Reliability,Cost effective,Multi objective optimization,Quality of service,PV,Solar pumps,Wind,Irrigation system,Rural development,Rural Electrification,Renewable energy system
更新于2025-09-11 14:15:04
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Single- and multi-objective optimization for photovoltaic distributed generators implementation in probabilistic power flow algorithm
摘要： In this study, probabilistic power flow (PPF) for radial distribution systems (RDSs) integrated with photovoltaic (PV) distributed generators (DGs) is presented. The PPF is carried out using a combined approach of cumulants generating function and Gram–Charlier expansion. To express the intermittent nature of the PV power generation and demand powers, the random probabilities for solar irradiance and load demand are considered and modeled in the PPF. The benefits of PVDGs integration into RDS can be accomplished by their optimal placement and sizing. Hence, two optimization approaches are implemented to allocate the PVDG in the RDS. The first optimization approach utilizes a single-objective function based on particle swarm optimization (PSO) to minimize the total power losses in RDSs, while the second approach uses the multi-objective PSO (MOPSO) to minimize the total power losses and voltage deviation. However, in case of MOPSO, a fuzzy logic decision making is developed to adopt a suitable solution from the optimal Pareto set according to the decision-maker preference. The developed algorithm is verified using two standard IEEE radial distribution systems: IEEE 33-bus and 69-bus. The obtained results prove the ability of the developed algorithm in solving the PPF considering the optimal PVDG allocation with low computational time.
关键词： Radial distribution systems,Probabilistic power flow,Distributed generation,Single- and multi-objective optimization
更新于2025-09-11 14:15:04
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Heart rate estimation using remote photoplethysmography with multi-objective optimization
摘要： Remote photoplethysmography (rPPG) is being increasingly used to measure heart rate from recorded or live videos. The rhythmic flow of arterial blood, referred to as the blood volume pulse, results in periodic variations in the skin color which are then quantified into a temporal signal for analysis. Independent Component Analysis (ICA) has been used to extract the blood volume pulse which is assumed to have been mixed into the RGB channels of the skin pixels. We propose a novel semi-blind source extraction method for measuring rPPG using a multi-objective optimization approach with autocorrelation as a periodicity measure. Our method was tested on our inhouse video database UBFC-RPPG and the MMSE-HR database [33]. Our in-house database is made publicly available and is specifically aimed towards testing rPPG measurements. Our method showed improved performance over other state of the art rPPG algorithms in terms of accuracy with all the databases.
关键词： Semi-blind source separation,Remote heart rate measurement,Constrained Independent Component Analysis,Multi-objective optimization,Independent Component Analysis,Remote photoplethysmography
更新于2025-09-10 09:29:36
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Economic and environmental potential for solar assisted central heating plants in the EU residential sector: Contribution to the 2030 climate and energy EU agenda
摘要： Aligning with the ambitious EU 2030 climate and energy package for cutting the greenhouse emissions and replacing conventional heat sources through the presence of renewable energy share inside efficient district heating fields, central solar heating plants coupled with seasonal storage (CSHPSS) can have a viable contribution to this goal. However, the technical performance variation combined with inadequate financial assessment and insufficient environmental impact data associated with the deployment of those innovative district heating systems represents a big challenge for the broad implementation of CSHPSS in Europe. In this context, our paper presents a comprehensive evaluation for the possibility of integrating CSHPSS in the residential sector in various EU member states through the formulation of a multi-objective optimization framework. This framework comprises the life cycle cost analysis for the economic evaluation and the life cycle assessment for the environmental impact estimation simultaneously. The technical performance is also considered by satisfying both the space heating demand and the domestic hot water services. The methodological framework is applied to a residential neighborhood community of 1120 apartments in various EU climate zones with Madrid, Athens, Berlin, and Helsinki acting as a proxy for the Mediterranean continental, Mediterranean, central European, and Nordic climates, respectively. The optimization results regarding the energy performance show that the CSHPSS can achieve a renewable energy fraction above 90% for the investigated climate zones. At the same time, the environmental assessment shows significant improvement when using the CSHPSS in comparison to a natural gas heating system, in those cases the environmental impact is reduced up to 82.1–86.5%. On the other hand, substantial economic improvement is limited, especially in the Mediterranean climate zone (Athens) due to low heating demands and the prices of the non-renewable resources. There the total economic cost of the CSHPSS plants can increase up to 50.8% compared to a natural gas heating system. However, considering the incremental tendency in natural gas prices all over EU nowadays, the study of future plant costs confirms its favorable long-term economic feasibility.
关键词： Life cycle assessment (LCA),2030 climate and energy EU targets,Multi-objective optimization,Life cycle cost (LCC),Central solar heating plant with seasonal storage,Solar community
更新于2025-09-10 09:29:36
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Towards Weakly Pareto Optimal: An Improved Multi-Objective Based Band Selection Method for Hyperspectral Imagery
摘要： Band selection refers to finding the most representative channels from hyperspectral images. Usually, certain objective functions are designed and combined via regularization terms. Owing to the parameters independence and the optimal solutions, multi-objective based methods have presented promising performance. However, the characteristics of the hyperspectral band selection problem make its range to be discrete. In this case, recently proposed weighted Tchebycheff based multi-objective band selection methods could only reach the weakly Pareto optimal, which would result in non-unique solutions. In this paper, we improve the decomposition process of the multi-objective based band selection method via a boundary intersection approach. Compared with weighted Tchebycheff decomposition, the proposed method is able to change the shape of the contour lines between Pareto Front and the ideal point, and this approach is particularly suitable for discrete-range problems. The effectiveness of our improvement is demonstrated by comparison experiments.
关键词： band selection,Multi-objective optimization,hyperspectral imagery
更新于2025-09-09 09:28:46
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[Institution of Engineering and Technology 12th European Conference on Antennas and Propagation (EuCAP 2018) - London, UK (9-13 April 2018)] 12th European Conference on Antennas and Propagation (EuCAP 2018) - Compact Dual-band Bow-tie MIMO Antennas with Fragment-type Isolation Structure
摘要： Compact dual-band bow-tie MIMO antennas with fragment-type isolation structure are presented. The proposed bow-tie MIMO antennas include both canonical structures defining the radiators and fragment structures isolator. In the design, MOEA/D-DE for defining the optimization of canonical structures and MOEA/D-GO for optimization of fragment structures are combined and iterated. After the compound optimization, both simulation and measurement show that the return loss is higher than 10dB and isolation is higher than 25dB in the dual bands of 2.45-2.75GHz and 3.35-3.9GHz. Based on the overall performance, the proposed array can be employed for MIMO wireless communication systems like WiMAX.
关键词： fragment-type isolation,dual-band antennas,multi-objective optimization
更新于2025-09-04 15:30:14
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[Institution of Engineering and Technology 12th European Conference on Antennas and Propagation (EuCAP 2018) - London, UK (9-13 April 2018)] 12th European Conference on Antennas and Propagation (EuCAP 2018) - Low-Cost Multi-Objective Optimization of Antennas By Means Of Generalized Pareto Ranking Bisection Algorithm
摘要： This paper introduces a generalized Pareto ranking bisection algorithm for low-cost multi-objective design optimization of antenna structures. The algorithm allows for identifying a set of Pareto optimal sets of parameters (that represent the best trade-offs between considered objectives) by iterative partitioning of the intervals connecting previously found designs and executing a Pareto-ranking-based poll search. The initial approximation of the Pareto front found using the bisection procedure is subsequently refined to the level of the high-fidelity EM model of the antenna at hand using local optimization. A serious limitation of the original bisection algorithm was that only two objectives could be considered. The generalized version proposed here allows for handling any number of design goals. An improved poll search procedure has also been developed and incorporated. Our algorithm has been demonstrated using an example of a UWB monopole antenna with three figures of interest taken into account: structure size, reflection response, and gain variability.
关键词： Antenna design,simulation-driven design,variable-fidelity simulations,generalized bisection algorithm,multi-objective optimization,Pareto ranking
更新于2025-09-04 15:30:14