標(biāo)題: Titlebook: Swarm Intelligence; 8th International Co Marco Dorigo,Mauro Birattari,Thomas Stützle Conference proceedings 2012 Springer-Verlag Berlin Hei [打印本頁(yè)] 作者: 有判斷力 時(shí)間: 2025-3-21 16:34
書目名稱Swarm Intelligence影響因子(影響力)
書目名稱Swarm Intelligence影響因子(影響力)學(xué)科排名
書目名稱Swarm Intelligence網(wǎng)絡(luò)公開度
書目名稱Swarm Intelligence網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Swarm Intelligence被引頻次
書目名稱Swarm Intelligence被引頻次學(xué)科排名
書目名稱Swarm Intelligence年度引用
書目名稱Swarm Intelligence年度引用學(xué)科排名
書目名稱Swarm Intelligence讀者反饋
書目名稱Swarm Intelligence讀者反饋學(xué)科排名
作者: 竊喜 時(shí)間: 2025-3-21 22:34 作者: 灰姑娘 時(shí)間: 2025-3-22 01:37 作者: galley 時(shí)間: 2025-3-22 08:31
https://doi.org/10.1007/978-3-642-32650-9algorithms; ant colony optimization; machine learning; particle swarm optimization; robotics; algorithm a作者: 男生戴手銬 時(shí)間: 2025-3-22 09:02 作者: 不能仁慈 時(shí)間: 2025-3-22 15:47 作者: 組成 時(shí)間: 2025-3-22 19:21 作者: cringe 時(shí)間: 2025-3-22 21:48
A Particle Swarm Embedding Algorithm for Nonlinear Dimensionality Reduction the embedding is evaluated with the nearest neighbor data space reconstruction error, and a co-ranking matrix based measure. Experimental studies show that PSEA achieves competitive or even better embeddings like the related methods locally linear embedding, and ISOMAP.作者: interior 時(shí)間: 2025-3-23 05:27
Hybrid Algorithms for the Minimum-Weight Rooted Arborescence Problemnamic programming, and can therefore be regarded as hybrid techniques. An extensive experimental evaluation shows that both algorithms generally improve over an exisiting heuristic from the literature.作者: 亞當(dāng)心理陰影 時(shí)間: 2025-3-23 08:02 作者: 道學(xué)氣 時(shí)間: 2025-3-23 10:57
Task Partitioning via Ant Colony Optimization for Distributed Assemblyteam of ants dividing a set of tasks, with pheromone marking connections between tasks guiding decisions on task allocation. We present simulation results for various 2-D and 3-D structures and discuss the advantages of the ACO formulation in the context of other existing approaches.作者: JADED 時(shí)間: 2025-3-23 15:23
The Self-adaptive Comprehensive Learning Particle Swarm Optimizerhe search commences. Application of the Self-Adaptive Comprehensive Learning Particle Swarm Optimizer (SACLPSO) to 9 well known test functions show an improvement in performance on most of the functions compared to CLPSO and a tuned PSO.作者: contrast-medium 時(shí)間: 2025-3-23 18:08 作者: conservative 時(shí)間: 2025-3-23 22:54
A “Thermodynamic” Approach to Multi-robot Cooperative Localization with Noisy Sensorsnts and by presenting a novel analysis based on the .assumption. The results of this paper are more precise than what was previously reported. Nevertheless, when considering the limit of a large group of robots, and after a long “stabilization” time, the final results turn out to be identical.作者: 變異 時(shí)間: 2025-3-24 05:56 作者: Expertise 時(shí)間: 2025-3-24 08:19 作者: 分解 時(shí)間: 2025-3-24 12:33 作者: senile-dementia 時(shí)間: 2025-3-24 15:27 作者: 溫和女人 時(shí)間: 2025-3-24 19:03 作者: bifurcate 時(shí)間: 2025-3-25 01:21
AcoSeeD: An Ant Colony Optimization for Finding Optimal Spaced Seeds in Biological Sequence Searchte. Experimental results demonstrate that AcoSeeD brings a significant improvement of sensitivity while demanding the same computational time as other state-of-the-art methods. We also introduces an alternative way of using local search that exerts a fast approximation of the objective function in ACO.作者: circumvent 時(shí)間: 2025-3-25 04:35 作者: 過(guò)時(shí) 時(shí)間: 2025-3-25 08:08 作者: antiquated 時(shí)間: 2025-3-25 15:39
Analysing Robot Swarm Decision-Making with Bio-PEPAe biochemical systems. Its main advantage is that it allows different kinds of analyses of a swarm robotics system starting from a single description. In general, to carry out different kinds of analysis, it is necessary to develop multiple models, raising issues of mutual consistency. With Bio-PEPA作者: 傳授知識(shí) 時(shí)間: 2025-3-25 17:59 作者: 詞匯表 時(shí)間: 2025-3-25 21:01
Bare Bones Particle Swarms with Jumpsgh Kennedy’s original formulation is not competitive to standard PSO, the addition of a component-wise jumping mechanism, and a tuning of the standard deviation, can produce a comparable optimisation algorithm. This algorithm, Bare Bones with Jumps, exists in a variety of formulations. Two particula作者: gregarious 時(shí)間: 2025-3-26 01:00
Hybrid Algorithms for the Minimum-Weight Rooted Arborescence Problemminent example is the automated reconstruction of consistent tree structures from noisy images. In this paper, we first propose a heuristic for tackling the minimum-weight rooted arborescence problem. Moreover, we propose an ant colony optimization algorithm. Both approaches are strongly based on dy作者: CHOIR 時(shí)間: 2025-3-26 06:32
Improving the ,Ant-Miner, Classification Algorithm-Miner, called .Ant-Miner., uses the ACO procedure in a different fashion. The main difference is that the search in .Ant-Miner. is optimised to find the best list of rules, whereas in Ant-Miner the search is optimised to find the best individual rule at each step of the sequential covering, produci作者: Lice692 時(shí)間: 2025-3-26 08:52 作者: ARENA 時(shí)間: 2025-3-26 16:19
Measuring Diversity in the Cooperative Particle Swarm OptimizerDiversity is closely linked to the exploration-exploitation tradeoff. High diversity facilitates exploration, which is usually required during the initial iterations of the optimization algorithm. A low diversity is indicative of exploitation of a small area of the search space, desired during the l作者: Sinus-Node 時(shí)間: 2025-3-26 19:49
Multi-armed Bandit Formulation of the Task Partitioning Problem in Swarm Roboticsrtitioning can be beneficial in terms of reduction of physical interference, increase of efficiency, higher parallelism, and exploitation of specialization. However, task partitioning also entails costs in terms of coordination efforts and overheads that can reduce its benefits. It is therefore impo作者: 放氣 時(shí)間: 2025-3-26 23:27 作者: dictator 時(shí)間: 2025-3-27 04:58 作者: Fibroid 時(shí)間: 2025-3-27 05:51
Task Partitioning via Ant Colony Optimization for Distributed Assemblytition general 2- and 3-D assembly tasks into N separate subtasks. The objective is to determine an allocation or partitioning strategy that minimizes the workload imbalance between the robots that allow for maximum assembly parallelization. This objective is achieved by extending ACO to apply to a 作者: 輕信 時(shí)間: 2025-3-27 10:46
The Self-adaptive Comprehensive Learning Particle Swarm Optimizer the particle swarm optimization (PSO) algorithm are critical to its success. This paper proposes that the control parameters of PSO be embedded in the position vector of particles and dynamically adapted while the search is in progress, relieving the user from specifying appropriate values before t作者: Felicitous 時(shí)間: 2025-3-27 14:37
Towards Swarm Calculus: Universal Properties of Swarm Performance and Collective Decisionsor artificial swarms. The ideal would be a ‘swarm calculus’ that allows to calculate key features such as expected swarm performance and robustness on the basis of a few parameters. A?path towards this ideal is to find methods and models that have maximal generality. We report two models that might 作者: Offbeat 時(shí)間: 2025-3-27 21:42
A Hybrid Particle Swarm Optimization Algorithm for the Open Vehicle Routing Problem popular supply chain management problems, the Open Vehicle Routing Problem. The Open Vehicle Routing Problem (OVRP) is a variant of the classic vehicle routing problem in which the vehicles do not return in the depot after the service of the customers. The proposed algorithm for the solution of the作者: 地殼 時(shí)間: 2025-3-27 23:45 作者: 辮子帶來(lái)幫助 時(shí)間: 2025-3-28 03:37 作者: 可以任性 時(shí)間: 2025-3-28 06:16
AcoSeeD: An Ant Colony Optimization for Finding Optimal Spaced Seeds in Biological Sequence Searchsed to improve the quality and sensitivity of searching, for example, in seeded alignment methods. Finding optimal spaced seeds is a NP-hard problem. In this study we introduce an application of an Ant Colony Optimization (ACO) algorithm to address this problem in a metaheuristics framework. This me作者: LOPE 時(shí)間: 2025-3-28 13:24 作者: 擁護(hù) 時(shí)間: 2025-3-28 16:24
Bare Bones Particle Swarms with Jumps deviation, can produce a comparable optimisation algorithm. This algorithm, Bare Bones with Jumps, exists in a variety of formulations. Two particular models are empirically examined in this paper and comparisons are made to canonical PSO and standard Bare Bones.作者: output 時(shí)間: 2025-3-28 20:12
Self-reconfigurable Modular e-pucksroup of e-pucks that are equipped with the extension. Our approach proves itself to be an effective method of coordinating the movement of a group of physically connected e-pucks. Furthermore, the system shows robustness in its ability to self-reconfigure and self-assemble following a disruption which alters the group’s structure.作者: 范例 時(shí)間: 2025-3-29 02:11 作者: BLANK 時(shí)間: 2025-3-29 07:06 作者: elucidate 時(shí)間: 2025-3-29 09:12 作者: PARA 時(shí)間: 2025-3-29 12:37 作者: Tdd526 時(shí)間: 2025-3-29 17:43
Sergi Mateo,Christian Blum,Pascal Fua,Engin Türetgen作者: fulcrum 時(shí)間: 2025-3-29 21:52
Matthew Medland,Fernando E. B. Otero,Alex A. Freitas作者: LASH 時(shí)間: 2025-3-30 03:28 作者: 全能 時(shí)間: 2025-3-30 07:42
Dong Do Duc,Huy Q. Dinh,Thanh Hai Dang,Kris Laukens,Xuan Huan Hoang作者: Arresting 時(shí)間: 2025-3-30 12:12 作者: 木質(zhì) 時(shí)間: 2025-3-30 15:49 作者: 歡騰 時(shí)間: 2025-3-30 16:55
Comparative Analysis of Machine-Learning and Deep Learning Algorithms Using Manta Ray Foraging Optimization for the Detection of Hate Speech,tion (HSD) using the Davidson’s dataset; a popular benchmark in this field. Count vectorization is used to preprocess textual data thereby enabling extraction of meaningful features. Various machine learning (ML) and deep learning (DL) architectures such as Support Vector Classifier (SVC), Long Shor作者: anaphylaxis 時(shí)間: 2025-3-31 00:13 作者: motivate 時(shí)間: 2025-3-31 01:24
Die reflexive Couch den Raum gestellt wurde, bündelt die irritierende Mischung aus methodischem Interesse und wissenschaftlicher Skepsis, die dem Verfahren der Feldforschungssupervision von Kolleg_innen h?ufig entgegengebracht wird.作者: ostrish 時(shí)間: 2025-3-31 06:23
2008 Mumbai Terrorist Attacks,ized hand-held weapons, and it was for this reason that the attacks were described as being a new type of terrorism. The attacks revealed a number of weaknesses in the capability of the police and in the analysis of intelligence.作者: Ebct207 時(shí)間: 2025-3-31 11:58
0302-9743 reconstruction, action recognition, video analysis and understanding, document analysis and recognition, biometrics, medical image analysis, and various applications..978-981-97-8492-9978-981-97-8493-6Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: exhilaration 時(shí)間: 2025-3-31 15:03 作者: 證明無(wú)罪 時(shí)間: 2025-3-31 20:13
Ignacy Gaw?dzki,Khaldoun Al Aghabut also the entire revised entry is reproduced so that the reader need not look for the previous entry in earlier volumes for the same substance. Thus, readers are advised to try to find the substance of interest first in this volume III/48 and then proceed backwards to volumes III/39, III/31 and I作者: Aerate 時(shí)間: 2025-3-31 22:07
Globalisierung als Innovationzierenden Unternehmen durch und best?tigen den Sachverhalt, dass wirtschaftliche T?tigkeit jeder Art nicht nur Chancen, sondern auch Risiken in sich birgt. Bei einer globalen Ausdehnung der Produktionen mit dem Ziel, Wachstum und Besch?ftigung zu erreichen, steigen zudem die Chancen und Risiken wirt作者: 歡樂中國(guó) 時(shí)間: 2025-4-1 05:36
Robert LeMoyne,Timothy Mastroianni,Donald Whiting,Nestor Tomycz anschlie?t? Eines kann man auf Anhieb sagen: Die ., d.h. der Wechselstromwiderstand dieser Serienschaltung (Abb. 6.01) ist bei hohen Frequenzen sehr gro?, weil die Induktivit?t der Spule keinen Strom hindurchl??t, und bei kleinen Frequenzen ebenfalls, weil die Kapazit?t sperrt. Dazwischen mu? . notwendigerweise ein Minimum haben.作者: 鑒賞家 時(shí)間: 2025-4-1 08:41
Vectors and MatricesWhat is a vector? It is a finite list of (real) numbers: scalars or components.作者: 易受刺激 時(shí)間: 2025-4-1 11:47 作者: 完成才能戰(zhàn)勝 時(shí)間: 2025-4-1 16:50
