Recently,urbanization becomes a major concern for developing as well as developed countries.Owing to the increased urbanization,one of the important challenging issues in smart cities is waste management.So,automated ...Recently,urbanization becomes a major concern for developing as well as developed countries.Owing to the increased urbanization,one of the important challenging issues in smart cities is waste management.So,automated waste detection and classification model becomes necessary for the smart city and to accomplish better recyclable waste management.Effective recycling of waste offers the chance of reducing the quantity of waste disposed to the land fill by minimizing the requirement of collecting raw materials.This study develops a novel Deep Consensus Network with Whale Optimization Algorithm for Recycling Waste Object Detection(DCNWORWOD)in Smart Cities.The goal of the DCNWO-RWOD technique intends to properly identify and classify the objects into recyclable and non-recyclable ones.The proposed DCNWO-RWOD technique involves the design of deep consensus network(DCN)to detect waste objects in the input image.For improving the overall object detection performance of the DCN model,the whale optimization algorithm(WOA)is exploited.Finally,Na飗e Bayes(NB)classifier is used for the classification of detected waste objects into recyclable and non-recyclable ones.The performance validation of theDCNWO-RWOD technique takes place using the open access dataset.The extensive comparative study reported the enhanced performance of the DCNWO-RWOD technique interms of several measures.展开更多
A fnite.-time consensus protocol is proposed for multi -dimensional multi- agent systems, using direction peserving signumcontrols. Flipp solutions and nonsmooh analysis tehniques are adopted to handle discontinuities...A fnite.-time consensus protocol is proposed for multi -dimensional multi- agent systems, using direction peserving signumcontrols. Flipp solutions and nonsmooh analysis tehniques are adopted to handle discontinuities. Suficient and ncessaryconditions are provided to guarantee infinte time convergence and boundedness of the solutions. It turns out that the numberof agents which have cotinuous contol law plays an ssenan role in fnite-tine conerence In adidio it is shown thatthe unit bals itoduced bylp, norms. where p ∈[1,∞] , are inariat for the closed lop.展开更多
A distributed energy management in a photovoltaic charging station(PV-CS) is proposed on the basis of different behavioural responses of electric vehicle(EV) drivers. On the basis of the provider or the consumer of th...A distributed energy management in a photovoltaic charging station(PV-CS) is proposed on the basis of different behavioural responses of electric vehicle(EV) drivers. On the basis of the provider or the consumer of the power, charging station and EVs have been modeled as independent players with different preferences. Because of the selfish behaviour of the individuals and their hierarchies, the power distribution problem is modeled as a noncooperative Stackelberg game. Moreover, Karush-Kuhn-Tucker(KKT) conditions and the most socially stable equilibrium are adopted to solve the problem in hand. The consensus network, a learning-based algorithm, is utilized to let the EVs communicate and update their own charging power in a distributed fashion. Simulation analysis is supported to show the static and dynamic responses as well as the effectiveness and workability of the proposed charging power management. For the sake of showing the responses of EV drivers, different behavioural responses of EVs’ drivers to the discount on the charging price offered by the station are introduced. The simulation results show the effectiveness of the proposed energy management.展开更多
In this paper, we address the characteristic model-based discrete-time consensus problem of networked robotic manipulators with dynamic uncertainties. The research objective is to achieve joint-position consensus of m...In this paper, we address the characteristic model-based discrete-time consensus problem of networked robotic manipulators with dynamic uncertainties. The research objective is to achieve joint-position consensus of multiple robotic agents interconnected on directed graphs containing a spanning tree. A novel characteristic model-based distributed adaptive control scenario is proposed with a state-relied projection estimation law and a characteristic model-based distributed controller. The performance analysis is also unfolded where the uniform ultimate boundedness(UUB) of consensus errors is derived by resorting to the discrete-time-domain stability analysis tool and the graph theory. Finally, numerical simulations illustrate the effectiveness of the proposed theoretical strategy.展开更多
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work under grant number(RGP2/42/43)Princess Nourah bint Abdulrahman UniversityResearchers Supporting Project number(PNURSP2022R114)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Recently,urbanization becomes a major concern for developing as well as developed countries.Owing to the increased urbanization,one of the important challenging issues in smart cities is waste management.So,automated waste detection and classification model becomes necessary for the smart city and to accomplish better recyclable waste management.Effective recycling of waste offers the chance of reducing the quantity of waste disposed to the land fill by minimizing the requirement of collecting raw materials.This study develops a novel Deep Consensus Network with Whale Optimization Algorithm for Recycling Waste Object Detection(DCNWORWOD)in Smart Cities.The goal of the DCNWO-RWOD technique intends to properly identify and classify the objects into recyclable and non-recyclable ones.The proposed DCNWO-RWOD technique involves the design of deep consensus network(DCN)to detect waste objects in the input image.For improving the overall object detection performance of the DCN model,the whale optimization algorithm(WOA)is exploited.Finally,Na飗e Bayes(NB)classifier is used for the classification of detected waste objects into recyclable and non-recyclable ones.The performance validation of theDCNWO-RWOD technique takes place using the open access dataset.The extensive comparative study reported the enhanced performance of the DCNWO-RWOD technique interms of several measures.
文摘A fnite.-time consensus protocol is proposed for multi -dimensional multi- agent systems, using direction peserving signumcontrols. Flipp solutions and nonsmooh analysis tehniques are adopted to handle discontinuities. Suficient and ncessaryconditions are provided to guarantee infinte time convergence and boundedness of the solutions. It turns out that the numberof agents which have cotinuous contol law plays an ssenan role in fnite-tine conerence In adidio it is shown thatthe unit bals itoduced bylp, norms. where p ∈[1,∞] , are inariat for the closed lop.
基金the Technology Projects of China State Grid Corporation(No.SGJS0000YXJS1800187)
文摘A distributed energy management in a photovoltaic charging station(PV-CS) is proposed on the basis of different behavioural responses of electric vehicle(EV) drivers. On the basis of the provider or the consumer of the power, charging station and EVs have been modeled as independent players with different preferences. Because of the selfish behaviour of the individuals and their hierarchies, the power distribution problem is modeled as a noncooperative Stackelberg game. Moreover, Karush-Kuhn-Tucker(KKT) conditions and the most socially stable equilibrium are adopted to solve the problem in hand. The consensus network, a learning-based algorithm, is utilized to let the EVs communicate and update their own charging power in a distributed fashion. Simulation analysis is supported to show the static and dynamic responses as well as the effectiveness and workability of the proposed charging power management. For the sake of showing the responses of EV drivers, different behavioural responses of EVs’ drivers to the discount on the charging price offered by the station are introduced. The simulation results show the effectiveness of the proposed energy management.
基金supported by the National Natural Science Foundation of China(Grant Nos.6133300861273153&61304027)
文摘In this paper, we address the characteristic model-based discrete-time consensus problem of networked robotic manipulators with dynamic uncertainties. The research objective is to achieve joint-position consensus of multiple robotic agents interconnected on directed graphs containing a spanning tree. A novel characteristic model-based distributed adaptive control scenario is proposed with a state-relied projection estimation law and a characteristic model-based distributed controller. The performance analysis is also unfolded where the uniform ultimate boundedness(UUB) of consensus errors is derived by resorting to the discrete-time-domain stability analysis tool and the graph theory. Finally, numerical simulations illustrate the effectiveness of the proposed theoretical strategy.
