標題: Titlebook: Advances in Swarm Intelligence; First International Ying Tan,Yuhui Shi,Kay Chen Tan Conference proceedings 2010 Springer-Verlag Berlin Hei [打印本頁] 作者: 固執(zhí)已見 時間: 2025-3-21 19:34
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: Lament 時間: 2025-3-21 21:32 作者: AVANT 時間: 2025-3-22 01:00
Ying Tan,Yuhui Shi,Kay Chen TanFast track conference proceedings.Unique visibility.State of the art research作者: 有特色 時間: 2025-3-22 05:51
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/a/image/149958.jpg作者: 盟軍 時間: 2025-3-22 10:29
M.-C. Desjonquères,D. Spanjaardibility distribution for the fuzzy variable. In this paper, we seek a similar characterization of the joint possibility distribution for a pair of fuzzy variables. In view of the success of introducing the expected value and variance as fuzzy integrals of appropriate functions of single fuzzy variab作者: 占線 時間: 2025-3-22 13:35 作者: 正論 時間: 2025-3-22 19:48
Electronic Structure of Surfaces,e validity index for network fuzzy clustering is proposed, which involves the compactness and separation measures for each cluster. The simulated annealing strategy is used to minimize this validity index, associating with a dissimilarity-index-based fuzzy .-means iterative procedure, under the fram作者: 從容 時間: 2025-3-22 21:54
M.-C. Desjonquères,D. Spanjaardce with fuzzy interference to build a fault diagnosis model, and use fuzzy network to improve the model. The result of simulation proved that this model can absorb the experiences of human and make accurate judgments; the trained fuzzy network has the same function and can reach the self-learning de作者: Congregate 時間: 2025-3-23 02:51
Overview of the reference model,x trace that controls the distances between the class centroids. Based on the principle of cluster centers separation, fuzzy cluster centers separation (FCCS) clustering is an extended fuzzy c-means (FCM) clustering algorithm. FCCS attaches importance to both the fuzzy within cluster scatter matrix 作者: 山羊 時間: 2025-3-23 07:42
Overview of the reference model,(E-S) model for portfolio optimization problem. Since the spread is defined by Lebesgue-Stieltjes (L-S) integral, its computation for general fuzzy variables is a challenge issue for research, and usually depends on approximation scheme and soft computing. But for frequently used trapezoidal and tri作者: paltry 時間: 2025-3-23 12:00
Application of the reference model, proposed. Using subtractive clustering and Particle Swarm Optimization (PSO)-hybrid algorithm as a tool for building the fault diagnosis model, then, the model of fault diagnosis system was used to the circuit fault diagnosis. Simulation results have shown that the method is more effective.作者: Munificent 時間: 2025-3-23 14:29 作者: Iniquitous 時間: 2025-3-23 21:50
Application of the reference model,sis of multiple-core-type modular producing network cooperation partner selection, this paper suggests that Comprehensive Evaluation Method to choose partners is to choose the multiple-core-type modular producing network cooperation partners in accordance with the principles of the lowest total cost作者: 粗魯性質(zhì) 時間: 2025-3-23 22:24
Application of the reference model,onomic development. Artificial Neural Networks (ANN) deal with information through interactions among neurons (or nodes), approximating the mapping between inputs and outputs based on non-linear functional composition. They have the advantages of self-learning, self-organizing, and self-adapting. It作者: VERT 時間: 2025-3-24 03:55
David Beech (Chairman of IFIP WG 2.7)k. The North American Electric Reliability Corporation (NERC) has thus developed several iterations of cyber security standards. According to the NERC cyber standards CIP-002-2 requirements, in this paper, we present cyber security risk analysis using computational intelligence methods and review on作者: 諄諄教誨 時間: 2025-3-24 06:53
David Beech (Chairman of IFIP WG 2.7)ssible which include 3 categories. The first is based on language model. We train our language model on four different corpora. The second resource is the syntax dependency relations, which are extracted by Minipar. And the third resource contains only one feature, the document score provided by Inf作者: browbeat 時間: 2025-3-24 11:19 作者: adjacent 時間: 2025-3-24 16:12 作者: MEAN 時間: 2025-3-24 19:44
Lecture Notes in Computer Science supply chains. Based on the model, scholars can study the management of make-to-order supply chains easily. Agents, who are used to simulate the members of supply chains, produce appropriate products by intelligent choices. The relationships among agents are connected by their products. Agents’ att作者: maverick 時間: 2025-3-25 03:05
https://doi.org/10.1007/3-540-16791-9petes customers in quality to price ratio. The value of prominent AdWords advertising position and the resulting price dispersion patterns are studied. We found that prominent position of an Ad words is not always favorite to all firms according to the analysis based on game theory. For the firm whi作者: ACTIN 時間: 2025-3-25 07:13
Application of the reference model,noisy heart signal are collected form MIT-BIH database. Then signals are transformed to frequency domain and cutoff frequency is calculated. Since heart signals are lowpass frequency, a Finite Impulse Response (FIR) filter is adequate to remove the noise. In the next step, a dataset is configured fo作者: 牽索 時間: 2025-3-25 07:56 作者: outskirts 時間: 2025-3-25 14:19 作者: Coterminous 時間: 2025-3-25 17:15
https://doi.org/10.1007/978-3-642-13498-2algorithms; computational intelligence; data mining; evolution; evolutionary computation; genetic algorit作者: Cardiac-Output 時間: 2025-3-25 21:56
978-3-642-13497-5Springer-Verlag Berlin Heidelberg 2010作者: Urgency 時間: 2025-3-26 03:11
Advances in Swarm Intelligence978-3-642-13498-2Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: FLUSH 時間: 2025-3-26 08:00 作者: Humble 時間: 2025-3-26 11:10
Application of the reference model, proposed. Using subtractive clustering and Particle Swarm Optimization (PSO)-hybrid algorithm as a tool for building the fault diagnosis model, then, the model of fault diagnosis system was used to the circuit fault diagnosis. Simulation results have shown that the method is more effective.作者: PAEAN 時間: 2025-3-26 16:06
On the Correlations between Fuzzy Variablesibility distribution for the fuzzy variable. In this paper, we seek a similar characterization of the joint possibility distribution for a pair of fuzzy variables. In view of the success of introducing the expected value and variance as fuzzy integrals of appropriate functions of single fuzzy variab作者: 石墨 時間: 2025-3-26 19:30
Modeling Fuzzy Data Envelopment Analysis with Expectation Criterionontains the credibility of fuzzy events in the constraints and the expected value of a fuzzy variable in the objective, the solution process is very complex. Thus, in the case when the inputs and outputs are mutually independent trapezoidal fuzzy variables, we discuss the equivalent nonlinear forms 作者: neurologist 時間: 2025-3-26 21:46 作者: Psa617 時間: 2025-3-27 04:52 作者: 分開 時間: 2025-3-27 07:10
Fuzzy Cluster Centers Separation Clustering Using Possibilistic Approachx trace that controls the distances between the class centroids. Based on the principle of cluster centers separation, fuzzy cluster centers separation (FCCS) clustering is an extended fuzzy c-means (FCM) clustering algorithm. FCCS attaches importance to both the fuzzy within cluster scatter matrix 作者: Madrigal 時間: 2025-3-27 10:15
A Class of Fuzzy Portfolio Optimization Problems: E-S Models(E-S) model for portfolio optimization problem. Since the spread is defined by Lebesgue-Stieltjes (L-S) integral, its computation for general fuzzy variables is a challenge issue for research, and usually depends on approximation scheme and soft computing. But for frequently used trapezoidal and tri作者: inundate 時間: 2025-3-27 13:52
Application of PSO-Adaptive Neural-fuzzy Inference System (ANFIS) in Analog Circuit Fault Diagnosis proposed. Using subtractive clustering and Particle Swarm Optimization (PSO)-hybrid algorithm as a tool for building the fault diagnosis model, then, the model of fault diagnosis system was used to the circuit fault diagnosis. Simulation results have shown that the method is more effective.作者: Occlusion 時間: 2025-3-27 20:05 作者: 后天習(xí)得 時間: 2025-3-27 22:54
Cooperation Partners Selection for Multiple-Core-Type MPNsis of multiple-core-type modular producing network cooperation partner selection, this paper suggests that Comprehensive Evaluation Method to choose partners is to choose the multiple-core-type modular producing network cooperation partners in accordance with the principles of the lowest total cost作者: 柏樹 時間: 2025-3-28 04:53 作者: 白楊魚 時間: 2025-3-28 06:18
Computational Intelligence Algorithms Analysis for Smart Grid Cyber Securityk. The North American Electric Reliability Corporation (NERC) has thus developed several iterations of cyber security standards. According to the NERC cyber standards CIP-002-2 requirements, in this paper, we present cyber security risk analysis using computational intelligence methods and review on作者: 調(diào)色板 時間: 2025-3-28 13:40
Using AOBP for Definitional Question Answeringssible which include 3 categories. The first is based on language model. We train our language model on four different corpora. The second resource is the syntax dependency relations, which are extracted by Minipar. And the third resource contains only one feature, the document score provided by Inf作者: A精確的 時間: 2025-3-28 15:26
Radial Basis Function Neural Network Based on PSO with Mutation Operation to Solve Function Approximthm. This algorithm combines Particle Swarm Optimization algorithm (PSO) with mutation operation to train RBFNN. PSO with mutation operation and genetic algorithm are respectively used to train weights and spreads of oRBFNN, which is traditional RBFNN with gradient learning in this article. Sum Squa作者: 蛤肉 時間: 2025-3-28 22:13 作者: 注意到 時間: 2025-3-28 23:45 作者: Abominate 時間: 2025-3-29 06:40 作者: 輕而薄 時間: 2025-3-29 08:32 作者: IVORY 時間: 2025-3-29 15:09
A System Identification Using DRNN Based on Swarm Intelligenceation during the past decade. In this paper, a learning algorithm for Original Elman neural networks (ENN) based on modified particle swarm optimization (MPSO), which is a swarm intelligent algorithm (SIA), is presented. MPSO and Elman are hybridized to form MPSO-ENN hybrid algorithm as a system ide作者: exophthalmos 時間: 2025-3-29 15:56
Force Identification by Using SVM and CPSO Techniqued utilizes a new SVM-CPSO model that hybridized the chaos particle swarm optimization (CPSO) technique and support vector machines (SVM) to tackle the problem of force identification. Both numerical simulations and experimental study are performed to demonstrate the effectiveness, robustness and app作者: Harridan 時間: 2025-3-29 22:41 作者: 帶子 時間: 2025-3-30 02:47
0302-9743 onstitute the proceedings of the International Conference on Swarm Intelligence (ICSI 2010) held in Beijing, the capital of China, during June 12-15, 2010. ICSI 2010 was the ?rst gathering in the world for researchers working on all aspects of swarm intelligence, and providedan academic forum for th作者: 袖章 時間: 2025-3-30 05:30
David Beech (Chairman of IFIP WG 2.7)lect parameters of SVR. The proposed approach is used for forecasting logistics demand of Shanghai, The experimental results show that the above method obtained lesser training relative error and testing relative error.作者: 誘拐 時間: 2025-3-30 10:15 作者: 斜坡 時間: 2025-3-30 14:27
Application of the reference model,tween inputs and outputs based on non-linear functional composition. They have the advantages of self-learning, self-organizing, and self-adapting. It is practical to use ANN technology to carry out forecast of surface runoff.作者: 羽毛長成 時間: 2025-3-30 17:01 作者: 制造 時間: 2025-3-30 21:40 作者: LAPSE 時間: 2025-3-31 04:13
Application of the reference model, problem of force identification. Both numerical simulations and experimental study are performed to demonstrate the effectiveness, robustness and applicability of the proposed method. It is potential that the proposed method is practical to the real-life application.作者: 先鋒派 時間: 2025-3-31 06:39
Chaos Optimization SVR Algorithm with Application in Prediction of Regional Logistics Demandlect parameters of SVR. The proposed approach is used for forecasting logistics demand of Shanghai, The experimental results show that the above method obtained lesser training relative error and testing relative error.作者: d-limonene 時間: 2025-3-31 12:09
Cooperation Partners Selection for Multiple-Core-Type MPNpartners is to choose the multiple-core-type modular producing network cooperation partners in accordance with the principles of the lowest total cost, the shortest reaction time and the minimum risk and through two stages of the initial selection of core partner and the comprehensive evaluation of core partner combination.作者: auxiliary 時間: 2025-3-31 16:08 作者: 支架 時間: 2025-3-31 18:12
CRPSO-Based Integrate-and-Fire Neuron Model for Time Series Predictiontraining the IFN model in order to enhance its approximation and generalization capabilities. The proposed CRPSO-based IFN model is used for Mackey-Glass time series prediction problem. The experimental results demonstrate the superiority of CRPSO-based model in efficiency and robustness over the PSO algorithm, BP algorithms and GA.作者: 一致性 時間: 2025-3-31 22:46
FIR Cutoff Frequency Calculating for ECG Signal Noise Removing Using Artificial Neural Networkrt signals are lowpass frequency, a Finite Impulse Response (FIR) filter is adequate to remove the noise. In the next step, a dataset is configured for a multilayer perceptron (MLP) training with feedforward algorithm. Finally, the MLP is trained and results of cutoff frequency calculation are shown.作者: Cryptic 時間: 2025-4-1 04:10 作者: FANG 時間: 2025-4-1 10:01 作者: 學(xué)術(shù)討論會 時間: 2025-4-1 13:07
Overview of the reference model,re Error (SSE) function is used to evaluate performance of three algorithms, oRBFNN, GA-RBFNN and MuPSO-RBFNN algorithms. Several experiments in function approximation show MuPSO-RBFNN is better than oRBFNN and GA-RBFNN.作者: 直覺沒有 時間: 2025-4-1 17:51
Lecture Notes in Computer Scienceributes are presented by their knowledge and four actions of agents are introduced in the paper. A foreign trade supply chain is simulated to show the availability of the agent-based model. The model should be available as a toolkit for the studying of the make-to-order supply chains.作者: Ovulation 時間: 2025-4-1 22:28
David Beech (Chairman of IFIP WG 2.7)ntifier. Simulation experiments show that MPSO-ENN is a more effective swarm intelligent hybrid algorithm (SIHA), which results in an identifier with the best trained model. Dynamic identification system (DIS) of the MPSO-ENN is obtained.作者: Capture 時間: 2025-4-2 00:50
Overview of the reference model,es a quadratic programming problem that can be solved by general purpose software or conventional optimization algorithms. Finally, we demonstrate the developed modeling idea via two numerical examples.作者: Fortuitous 時間: 2025-4-2 05:09
https://doi.org/10.1007/3-540-16791-9ractiveness of the prominent Ad place depends on the market structure in terms of consumer preference and consumer search behavior. The more consumers purchase from the firm listed in the prominent Ad places or the more consumers prefer high-quality product the more strict area in which the low-quality product manufacture has positive profit.作者: 悠然 時間: 2025-4-2 09:58
A Class of Fuzzy Portfolio Optimization Problems: E-S Modelses a quadratic programming problem that can be solved by general purpose software or conventional optimization algorithms. Finally, we demonstrate the developed modeling idea via two numerical examples.作者: 案發(fā)地點 時間: 2025-4-2 12:52 作者: Mediocre 時間: 2025-4-2 15:39 作者: Lacunar-Stroke 時間: 2025-4-2 20:24
Finding and Evaluating Fuzzy Clusters in Networksonging to different clusters during the cooling process. An appropriate number of clusters can be automatically determined without any prior knowledge about the network structure. The computational results on several artificial and real-world networks confirm the capability of the algorithm.
