This study aims to solve the Nash equilibrium(NE) seeking problem for monotone N-coalition games. The authors assume that the gradient mapping of the game is monotone but not necessarily strictly or strongly monotone....
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This study aims to solve the Nash equilibrium(NE) seeking problem for monotone N-coalition games. The authors assume that the gradient mapping of the game is monotone but not necessarily strictly or strongly monotone. Such a merely monotone assumption presents significant challenges to NE seeking, since the basic gradient descent method may fail to converge. The authors start with a regularization-based projected gradient dynamical system in a general non-cooperative game framework and analyze the convergence of the dynamics under different scenarios. Then, the authors develop NE seeking algorithms for monotone N-coalition games with undirected and connected inner-coalition communication graphs. Asymptotic convergence to the least-norm NE is proven. The convergence rate of the algorithm for an analytic mapping is provided. Furthermore, the authors propose a novel regularization-based dynamical system that allows different parameters among the coalitions. Rigorous analysis and a numerical example are provided to illustrate the effectiveness of the proposed method.
The research aims to investigate the impact of GO and ZnO nanoparticles in a 20% mahua biodiesel blend (B20) on direct injection diesel engine performance. Mahua oil, selected for its non-edible source and local avail...
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The research aims to investigate the impact of GO and ZnO nanoparticles in a 20% mahua biodiesel blend (B20) on direct injection diesel engine performance. Mahua oil, selected for its non-edible source and local availability, provides a sustainable fuel option. To improve combustion and reduce emissions, nanoparticles are added. Artificial neural networks (ANNs) and response surface methodology (RSM) are then used to predict and optimize engine operating parameters, leveraging their ability to model intricate relationships and analyze experimental data, ultimately aiming to create a more efficient and environmentally friendly fuel system. At a concentration of 75 ppm, GO and ZnO nanoparticles were taken into consideration. Additionally, a dispersant (TWEEN 80) and surfactant (CTAB) were mixed respectively at a ratio of 1:1. Using a spectrophotometer, stability analysis was carried out on different nanofuel samples, and a study based on experiments was done on a diesel engine. The output factors examined are BSFC, BTE, NHRR, CP, UHC, CO, NOx, and smoke Opacity. These metrics were based on performance, combustion, and emission characteristics. Input parameters such as fuel samples, injection pressure, and engine load were considered. The injection pressure varied at 200, 225, and 250 bar, whereas the load was considered to be 5%, 50%, 75%, and 100%, respectively. When compared to other fuel samples, dispersant included GO and ZnO nanoparticles in B20 shown optimal results. The B20 + GO 75 ppm + TWEEN 80 75 ppm combination has shown a 5.293% decrease in BSFC and 5.067% improvement in BTE at 250 bars. Furthermore, significant improvements were observed in key combustion parameters, CP increased by 3.13%, and NHRR increased by a substantial 43.50%. CO, UHC, NOx, and smoke opacity were all reduced by around 11.07%, 37.63%, 27.77%, and 38.55% respectively. With R2 values consistently between 0.93 and 0.99, the ANN and RSM predictions demonstrate a perfect fit to the data,
Classifying scenes and aerial imagery is a critical component in applications such as land-use analysis, land cover mapping, and remote sensing technologies. Numerous existing models leverage Convolutional Neural Netw...
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A combination of experimental and statistical analysis presents a comprehensive understanding of the microwave pyrolysis technique for catalytic deconstruction of mixed-density *** optimizing the process parameters an...
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A combination of experimental and statistical analysis presents a comprehensive understanding of the microwave pyrolysis technique for catalytic deconstruction of mixed-density *** optimizing the process parameters and catalyst selection,it is possible to maximize the production of valuable solid and energy products,contributing to sustainable waste *** this work,different mixed-density plastics were pyrolyzed with different catalysts and residence times to yield liquid fuel,syngas,and structured carbon *** effect of inputs on the product type,yield and composition was statistically evaluated using ANOVA,which showed an F value of 4.108 and a p-value of 0.098(>1.00).FTIR and GC-MS revealed that the oil product consisted of C13+fractions in the form of alkanes,alkenes,and *** microscopic analysis of the residue confirmed the formation of carbon nanotubes along with other amorphous *** presence of impurities in the solid product was further analyzed through XRD *** pyrolytic liquid fuel revealed the presence of conjugated aromatic structure and carbonyl group in their *** research demonstrated that converting mixed-density plastics using sodium zeolite,aluminum oxide,and nickel oxide catalysts yields 84%valuable products,confirming wasted plastics as a lucrative energy feedstock for producing hydrogen and high-value carbon compounds.
This study presents a general optimal trajectory planning(GOTP)framework for autonomous vehicles(AVs)that can effectively avoid obstacles and guide AVs to complete driving tasks safely and ***,we employ the fifth-orde...
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This study presents a general optimal trajectory planning(GOTP)framework for autonomous vehicles(AVs)that can effectively avoid obstacles and guide AVs to complete driving tasks safely and ***,we employ the fifth-order Bezier curve to generate and smooth the reference path along the road *** coordinates are then transformed to achieve the curvature continuity of the generated *** the road constraints and vehicle dynamics,limited polynomial candidate trajectories are generated and smoothed in a curvilinear coordinate ***,in selecting the optimal trajectory,we develop a unified and auto-tune objective function based on the principle of least action by employing AVs to simulate drivers’behavior and summarizing their manipulation characteristics of“seeking benefits and avoiding losses.”Finally,by integrating the idea of receding-horizon optimization,the proposed framework is achieved by considering dynamic multi-performance objectives and selecting trajectories that satisfy feasibility,optimality,and *** simulations and experiments are performed,and the results demonstrate the framework’s feasibility and effectiveness,which avoids both dynamic and static obstacles and applies to various scenarios with multi-source interactive traffic ***,we prove that the proposed method can guarantee real-time planning and safety requirements compared to drivers’manipulation.
In video games, procedural content generation has a strong history. Current procedural content generation strategies, such as search-based, solver-based, rule-based, and language-based techniques, have been used to cr...
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Data-driven process monitoring is an effective approach to assure safe operation of modern manufacturing and energy systems, such as thermal power plants being studied in this work. Industrial processes are inherently...
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Data-driven process monitoring is an effective approach to assure safe operation of modern manufacturing and energy systems, such as thermal power plants being studied in this work. Industrial processes are inherently dynamic and need to be monitored using dynamic algorithms. Mainstream dynamic algorithms rely on concatenating current measurement with past data. This work proposes a new, alternative dynamic process monitoring algorithm, using dot product feature analysis(DPFA).DPFA computes the dot product of consecutive samples, thus naturally capturing the process dynamics through temporal correlation. At the same time, DPFA's online computational complexity is lower than not just existing dynamic algorithms, but also classical static algorithms(e.g., principal component analysis and slow feature analysis). The detectability of the new algorithm is analyzed for three types of faults typically seen in process systems:sensor bias, process fault and gain change fault. Through experiments with a numerical example and real data from a thermal power plant, the DPFA algorithm is shown to be superior to the state-of-the-art methods, in terms of better monitoring performance(fault detection rate and false alarm rate) and lower computational complexity.
The development of communication technology will promote the application of Internet of Things,and Beyond 5G will become a new technology *** the same time,Beyond 5G will become one of the important supports for the d...
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The development of communication technology will promote the application of Internet of Things,and Beyond 5G will become a new technology *** the same time,Beyond 5G will become one of the important supports for the development of edge computing *** paper proposes a communication task allocation algorithm based on deep reinforcement learning for vehicle-to-pedestrian communication scenarios in edge *** trial and error learning of agent,the optimal spectrum and power can be determined for transmission without global information,so as to balance the communication between vehicle-to-pedestrian and *** results show that the agent can effectively improve vehicle-to-infrastructure communication rate as well as meeting the delay constraints on the vehicle-to-pedestrian link.
This research aimed to design a sea pimp-shaped monopole antenna by using etching and cutting techniques, combined with the addition of reflector, to modify the antenna structure to support the bandwidth standard acco...
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The objective of this research was to determine the mechanical parameter from EVA foam and also investigate its behavior by using Blatz-Ko,Neo-Hookean,Mooney model and experimental *** physical characteristic of EVA f...
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The objective of this research was to determine the mechanical parameter from EVA foam and also investigate its behavior by using Blatz-Ko,Neo-Hookean,Mooney model and experimental *** physical characteristic of EVA foam was also evaluated by scanning electron microscopy(SEM).The results show that Blatz-Ko and Neo-Hookean model can fit the curve at 5%and 8%strain,*** Mooney model can fit the curve at 50%*** modulus of rigidity evaluated from Mooney model is 0.0814±0.0027 *** structure of EVA foam from SEM image shows that EVA structure is a closed cell with homogeneous porous *** the result,it is found that Mooney model can adjust the data better than other *** model can be applied for mechanical response prediction of EVA foam and also for reference value in engineering application.
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