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Sustainability Measurement of Farming System in Isfahan Agricultural Sector (Smallholders-Rural Production Cooperatives- Farm Corporation)
Published 2016-10-01“…In Iran, the biggest obstacle to the agricultural development and the realization of its strategic goals and structural barriers are related to farming systems. The optimal use of soil and water resources and increase production and productivity per unit, improve the quality of agricultural products through the land consolidation,training, promotion and application of modern agricultural science and technology, promotion of mechanization, scientific management, proper use of existing facilities with an emphasis on restoring an preserving the environment and prevent the destruction or waste of resources changing the hardware systems and even removing barriers, expand the area under cultivation or solving this structural problem, the creation of a qualitative transformation in the structure of agriculture, especially in agricultural systems are related to farming system. 2- Material and Methods As a matter of fact, it was impossible to collect data of 17362, 635, and 85405 farmers belonged to agriculture cooperatives, farm corporation and smallholder farmers, respectively due to geographical scope of the research included the province of Isfahan, and the widespread distribution of the statistical population. …”
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An Adaptive Parameter Evolutionary Marine Predators Algorithm for Joint Resource Scheduling of Cooperative Jamming Networked Radar Systems
Published 2025-04-01“…Considering the scene constraints, an Improved Adaptive Parameter Evolution Marine Predators Algorithm is designed as an optimizer and embedded in the proposed framework to jointly optimize the platform beam allocation and jamming mode selection. …”
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104
Selecting the Strategic Port of “the Belt and Road” Based on the Global Network
Published 2021-01-01“…Under “the Belt and Road” initiative, China promoted cooperation between domestic enterprises and international ports vigorously, which brought back fruitful results, while the rational selection of strategic pivots ports and the optimization of the layout of the port network are important guarantees to a further promotion to the economic development of “the Belt and Road” ports and give full play to the driving and radiation role of strategic pivots ports. …”
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105
Distributed Cooperative Disturbance-Rejection Control of Hybrid Alternating Current/Direct Current Distribution Grids with Multiple Inverters
Published 2025-05-01“…To ensure the dynamic performance of the distributed controller, an optimal topology selection method is proposed based on the graph theory and network control system. …”
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106
Choose Your Partner: Social Evaluation of Skillfulness at Cooperative Co-Action Tasks in Tonkean Macaques (Macaca tonkeana)
Published 2025-08-01“…In this study, we investigated whether Tonkean macaques, Macaca tonkeana, can spontaneously use information, acquired by observation, to choose the optimal human partners for cooperation in two co-action tasks from the same domain. …”
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107
A Cooperative Planning Method for Multi-Type Charging Pile Station Based on Vehicle-Road-Network Coupling
Published 2025-07-01Get full text
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108
Multiobjective Cognitive Cooperative Jamming Decision-Making Method Based on Tabu Search-Artificial Bee Colony Algorithm
Published 2018-01-01“…Simulation results show that the search ability and probability of finding the optimal solution of the new algorithm are better than the other two. …”
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109
Quantification of selected SDGs in the context of China's climate mitigation pathway
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110
Physical layer security performance of MF relay selection systems
Published 2021-09-01“…Aimed at the poor security performance of single antenna multi-relay modify-and-forward (MF) cooperative wireless systems in collusion eavesdropping scenario, MF cooperative physical layer security systems combining source node transmit antenna selection (TAS) and multi-relay selection in collusion eavesdropping scenario were proposed.Two relay selection schemes were considered, namely, the optimal maximization of the main channel signal-to-noise ratio (SNR) and the suboptimal maximization of the source-relay link SNR.The closed-form expressions of the secrecy outage probability (SOP) and ergodic secure capacity (ESC) for the above MF cooperative wireless systems were derived.The numerical results of SOP and ESC of MF secure relay systems with optimal or suboptimal relay selection were consistent with the simulation results, which verifies the correctness of the above theoretical analysis.It also shows that the more the number of transmit antennas at the source node and relay nodes, and the less the number of eavesdropping nodes, the better the physical layer security performance of MF secure relay systems with optimal or suboptimal relay selection.…”
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111
Physical layer security performance of MF relay selection systems
Published 2021-09-01“…Aimed at the poor security performance of single antenna multi-relay modify-and-forward (MF) cooperative wireless systems in collusion eavesdropping scenario, MF cooperative physical layer security systems combining source node transmit antenna selection (TAS) and multi-relay selection in collusion eavesdropping scenario were proposed.Two relay selection schemes were considered, namely, the optimal maximization of the main channel signal-to-noise ratio (SNR) and the suboptimal maximization of the source-relay link SNR.The closed-form expressions of the secrecy outage probability (SOP) and ergodic secure capacity (ESC) for the above MF cooperative wireless systems were derived.The numerical results of SOP and ESC of MF secure relay systems with optimal or suboptimal relay selection were consistent with the simulation results, which verifies the correctness of the above theoretical analysis.It also shows that the more the number of transmit antennas at the source node and relay nodes, and the less the number of eavesdropping nodes, the better the physical layer security performance of MF secure relay systems with optimal or suboptimal relay selection.…”
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112
Allocation Strategy Optimization Using Repulsion-Enhanced Quantum Particle Swarm Optimization for Multi-AUV Systems
Published 2024-12-01“…The Nash equilibrium derived from the game analysis serves as the optimal solution for resource distribution in multi-AUV non-cooperative scenarios. …”
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113
Energy-Efficient Node Selection for Target Tracking in Wireless Sensor Networks
Published 2013-01-01“…This paper presents an energy-efficient selection of cooperative nodes. In the proposed method, the target detection probability is estimated by single-node processing based on particle filter. …”
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Proposing a template for selecting the coordinates of laboratory standards for executive management of the country.
Published 2025-02-01“…Abstract The aim of this study is to present a model for optimal selecting the characteristics of policy laboratories in the country's executive management. …”
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116
Transformation of Settlement Structures in Europe: Trends, Challenges, and Reform Approaches
Published 2025-01-01Get full text
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117
Optimal Management in the Operation of Complex Technical Systems
Published 2024-06-01“…Developing a cost management system for a complex technical system (CTS) at the stages of its life cycle is a modern trend aimed at creating sustainable cooperation ties based on requirements, including those of manufacturers and consumers. …”
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The role of response elements organization in transcription factor selectivity: the IFN-β enhanceosome example.
Published 2011-06-01“…Our molecular dynamics (MD) simulations on different motif combinations from the enhanceosome illustrate that cooperativity is achieved via unique organization of the REs: specific binding of one TF can enhance the binding of another TF to a neighboring RE and restrict others, through overlap of REs; the order of the REs can determine which complexes will form; and the alternation of consensus and non-consensus REs can regulate binding specificity by optimizing the interactions among partners. …”
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120
Robust reinforcement learning algorithm based on pigeon-inspired optimization
Published 2022-10-01“…Reinforcement learning(RL) is an artificial intelligence algorithm with the advantages of clear calculation logic and easy expansion of the model.Through interacting with the environment and maximizing value functions on the premise of obtaining little or no prior information, RL can optimize the performance of strategies and effectively reduce the complexity caused by physical models .The RL algorithm based on strategy gradient has been successfully applied in many fields such as intelligent image recognition, robot control and path planning for automatic driving.However, the highly sampling-dependent characteristics of RL determine that the training process needs a large number of samples to converge, and the accuracy of decision making is easily affected by slight interference that does not match with the simulation environment.Especially when RL is applied to the control field, it is difficult to prove the stability of the algorithm because the convergence of the algorithm cannot be guaranteed.Considering that swarm intelligence algorithm can solve complex problems through group cooperation and has the characteristics of self-organization and strong stability, it is an effective way to be used for improving the stability of RL model.The pigeon-inspired optimization algorithm in swarm intelligence was combined to improve RL based on strategy gradient.A RL algorithm based on pigeon-inspired optimization was proposed to solve the strategy gradient in order to maximize long-term future rewards.Adaptive function of pigeon-inspired optimization algorithm and RL were combined to estimate the advantages and disadvantages of strategies, avoid solving into an infinite loop, and improve the stability of the algorithm.A nonlinear two-wheel inverted pendulum robot control system was selected for simulation verification.The simulation results show that the RL algorithm based on pigeon-inspired optimization can improve the robustness of the system, reduce the computational cost, and reduce the algorithm’s dependence on the sample database.…”
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