標題: Titlebook: Advances in Swarm Intelligence; 13th International C Ying Tan,Yuhui Shi,Ben Niu Conference proceedings 2022 Springer Nature Switzerland AG [打印本頁] 作者: Disaster 時間: 2025-3-21 18:33
書目名稱Advances in Swarm Intelligence影響因子(影響力)
書目名稱Advances in Swarm Intelligence影響因子(影響力)學(xué)科排名
書目名稱Advances in Swarm Intelligence網(wǎng)絡(luò)公開度
書目名稱Advances in Swarm Intelligence網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Advances in Swarm Intelligence被引頻次
書目名稱Advances in Swarm Intelligence被引頻次學(xué)科排名
書目名稱Advances in Swarm Intelligence年度引用
書目名稱Advances in Swarm Intelligence年度引用學(xué)科排名
書目名稱Advances in Swarm Intelligence讀者反饋
書目名稱Advances in Swarm Intelligence讀者反饋學(xué)科排名
作者: 甜瓜 時間: 2025-3-21 23:24 作者: micronized 時間: 2025-3-22 01:37 作者: 光亮 時間: 2025-3-22 05:54 作者: Detonate 時間: 2025-3-22 10:27 作者: Proclaim 時間: 2025-3-22 16:30 作者: 小母馬 時間: 2025-3-22 18:32 作者: Abduct 時間: 2025-3-22 22:58 作者: 摸索 時間: 2025-3-23 03:54 作者: LANCE 時間: 2025-3-23 08:36
Cooperative Positioning Enhancement for?HDVs and?CAVs Coexisting Environment Using Deep Neural Netwoccuracy of vehicles with different positioning capabilities. Experimental results show the accuracy and timeliness of our proposal for enhancing vehicle positioning accuracy and sharing vehicle positioning information.作者: 光滑 時間: 2025-3-23 12:58
Task Offloading Decision Algorithm for Vehicular Edge Network Based on Multi-dimensional Informationxperiments show that the task offloading decision model trained by the hybrid neural network in this paper has high validity and accuracy when making the offloading decision and can significantly reduce system overhead and task computing delay.作者: 機械 時間: 2025-3-23 16:38
Adversarial Examples Are Closely Relevant to?Neural Network Models - A Preliminary Experiment Explorl examples are closely related to them. Peculiarly, sensitivity’s property could help us distinguish the adversarial examples from the data set. This work will inspire the research of adversarial examples detection.作者: 蘆筍 時間: 2025-3-23 20:29 作者: hermitage 時間: 2025-3-23 22:42
0302-9743 ce, ICSI 2022, which took place in Xi’an, China, in July 2022. The theme of this year’s conference was “Serving Life with Swarm Intelligence”.. The 85 full papers presented were carefully reviewed and selected from 171 submissions. The papers of the second part cover topics such as: Swarm Robotics a作者: 全神貫注于 時間: 2025-3-24 02:38
Branch and Cut Algorithm for QCL-C topology and rapid convergence of a star topology. HT-PSO does not require any prior knowledge of the environment, thus it has stronger robustness and adaptability. Experimental results show its superior performance over the state-of-the-art multi-source location method.作者: 顯微鏡 時間: 2025-3-24 09:51 作者: guzzle 時間: 2025-3-24 12:53
https://doi.org/10.1007/b101764raditional APF. Therefore, we propose a new controller based on the improved APF. Then, the Lyapunov stability of the designed controller is analyzed. Simulation results show the effectiveness of the proposed controller and its superiority over the original method.作者: 作繭自縛 時間: 2025-3-24 18:13
Problems with Quadratic Capacity Constraintser is applied to a dataset from three data collection stations to predict several indicators. Experiments on real-world data sets and results demonstrate that the improvements proposed in this paper make the model perform better compared to both the original and other common models.作者: 外星人 時間: 2025-3-24 20:12 作者: 元音 時間: 2025-3-25 02:49
Conference proceedings 2022022, which took place in Xi’an, China, in July 2022. The theme of this year’s conference was “Serving Life with Swarm Intelligence”.. The 85 full papers presented were carefully reviewed and selected from 171 submissions. The papers of the second part cover topics such as: Swarm Robotics and Multi-a作者: Antigen 時間: 2025-3-25 05:23 作者: 語源學(xué) 時間: 2025-3-25 08:47 作者: 紋章 時間: 2025-3-25 15:14 作者: Entrancing 時間: 2025-3-25 18:46
An Improved Convolutional LSTM Network with?Directional Convolution Layer for?Prediction of?Water Quer is applied to a dataset from three data collection stations to predict several indicators. Experiments on real-world data sets and results demonstrate that the improvements proposed in this paper make the model perform better compared to both the original and other common models.作者: gait-cycle 時間: 2025-3-25 23:10 作者: A簡潔的 時間: 2025-3-26 01:33
https://doi.org/10.1007/978-3-031-09726-3computer networks; computer systems; computer vision; correlation analysis; evolutionary algorithms; gene作者: 雜役 時間: 2025-3-26 05:35
978-3-031-09725-6Springer Nature Switzerland AG 2022作者: Repatriate 時間: 2025-3-26 10:51
Problems with Linear Capacity Constraints mapping with replanning feature is still a challenge for autonomous robot navigation. In this paper, a new framework in light of the replanning-based methodology of concurrent mapping and path planning is proposed. It initially performs global path planning through a developed Gravitational Search 作者: 單片眼鏡 時間: 2025-3-26 13:56 作者: 迅速成長 時間: 2025-3-26 18:30 作者: cylinder 時間: 2025-3-26 21:41 作者: 治愈 時間: 2025-3-27 04:35 作者: Horizon 時間: 2025-3-27 08:27
Problems with Quadratic Capacity Constraintsation may be achieved, due to such parameters of motion, as swarm azimuth angle and velocity of movement may be set only for the master robot, while slave robots follow master one at the pre-determined distance. The flowchart of the swarm control system is worked out, according which all slave robot作者: 工作 時間: 2025-3-27 11:49
QCL-C: Relaxations and Special Casesiple waypoints that it achieves multiple-objective optimizations. Such multiple-objective optimizations include robot travelling distance minimization, time minimization, turning minimization, etc. In this paper, a particle swarm optimization (PSO) algorithm incorporated with a Generalized Voronoi d作者: 笨拙的你 時間: 2025-3-27 13:41
https://doi.org/10.1007/b101764erations. Most previous quantization approaches are not applicable to this task since they rely on full-precision gradients to update network weights. To fill this gap, in this work we advocate using Evolutionary Algorithms (EAs) to search for the optimal low-bits weights of DNNs. To efficiently sol作者: Calculus 時間: 2025-3-27 19:54 作者: Parley 時間: 2025-3-27 23:25 作者: FLACK 時間: 2025-3-28 05:14 作者: interrupt 時間: 2025-3-28 09:18
Branch and Cut Algorithm for QCL-Caper investigates the problem of the global asymptotic stability of stochastic neutral Hopfield neural networks with multiple time-varying delays. Different form the previous reported results, the neural networks are affected by not only stochastic perturbations, but also the time delays including d作者: craven 時間: 2025-3-28 11:39
Branch and Cut Algorithm for QCL-Cted independent decision. Nevertheless, the network state considered in the decision is single and lacks global information, which is not conducive to the overall optimization of the system. Therefore, this paper proposes a task offloading decision algorithm for vehicular edge network based on deep 作者: 刀鋒 時間: 2025-3-28 18:33
Branch and Cut Algorithm for QCL-Ces have paid close attention to adversarial examples: many research outcomes, e.g., adversarial and defensive approaches and algorithms. However, numerous people are still baffled about how adversarial examples affect neural networks. We present hypotheses and devise extensive experiments to acquire作者: 有花 時間: 2025-3-28 21:29
The FLATCON System from Concentrix Solar,a for variety tasks, including node classification, link prediction and graph classification. However, GNNs are vulnerable to adversarial attacks, i.e., a small perturbation to the graph structure and node features in wild setting can lead to non-trivial performance degradation. Non-robustness is on作者: ORBIT 時間: 2025-3-29 01:41 作者: 巫婆 時間: 2025-3-29 03:35 作者: Innovative 時間: 2025-3-29 07:59 作者: 分貝 時間: 2025-3-29 12:46
A Bio-Inspired Neural Network Approach to?Robot Navigation and?Mapping with?Nature-Inspired Algorith mapping with replanning feature is still a challenge for autonomous robot navigation. In this paper, a new framework in light of the replanning-based methodology of concurrent mapping and path planning is proposed. It initially performs global path planning through a developed Gravitational Search 作者: archetype 時間: 2025-3-29 15:45 作者: 細胞膜 時間: 2025-3-29 23:13
Advances in Cooperative Target Searching by Multi-UAVsrection with difficult in this field. To illustrate the progress of cooperative target searching by multi-UAVs, firstly, the significance of cooperative searching and its application in military and civil fields are systematically described. Then the current research status of the multi-UAVs coopera作者: 改正 時間: 2025-3-30 03:02 作者: 控制 時間: 2025-3-30 05:49
An Efficient Scheduling and?Navigation Approach for?Warehouse Multi-Mobile Robotsbased scheduling and navigation method for multi-mobile robots. In order to solve the problem of multi-robot multi-task point assignment in the warehouse environment, we establish a target model that minimizes the total transportation time and propose a hierarchical Genetic Algorithm-Ant Colony Opti作者: 不可磨滅 時間: 2025-3-30 11:24
Self-organizing Mobile Robots Swarm Movement Control Simulationation may be achieved, due to such parameters of motion, as swarm azimuth angle and velocity of movement may be set only for the master robot, while slave robots follow master one at the pre-determined distance. The flowchart of the swarm control system is worked out, according which all slave robot作者: jungle 時間: 2025-3-30 12:45 作者: 高貴領(lǐng)導(dǎo) 時間: 2025-3-30 18:54
Training Quantized Deep Neural Networks via?Cooperative Coevolutionerations. Most previous quantization approaches are not applicable to this task since they rely on full-precision gradients to update network weights. To fill this gap, in this work we advocate using Evolutionary Algorithms (EAs) to search for the optimal low-bits weights of DNNs. To efficiently sol作者: 聯(lián)想 時間: 2025-3-30 21:24 作者: 闡釋 時間: 2025-3-31 03:28 作者: 嫌惡 時間: 2025-3-31 06:31 作者: 祖先 時間: 2025-3-31 12:09
