標(biāo)題: Titlebook: Advances in Swarm Intelligence; 8th International Co Ying Tan,Hideyuki Takagi,Ben Niu Conference proceedings 2017 Springer International Pu [打印本頁] 作者: Addiction 時間: 2025-3-21 16:15
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: 乳汁 時間: 2025-3-21 22:35 作者: 語言學(xué) 時間: 2025-3-22 02:18 作者: Carcinogen 時間: 2025-3-22 05:40 作者: badinage 時間: 2025-3-22 09:48
Silvia Zorzetto,Francesco Ferraroults indicate that there is no statistical significant difference in performance between these two approaches. However, depending on the multi-objective evolutionary algorithm (MOEA) one approach does provide slightly better solutions than the other approach.作者: 代理人 時間: 2025-3-22 15:27
Conceptions of Giftedness and Talentthe positive posts themselves. In product recommendations with various emotional words, positive emotional recommendations are able to achieve better recommendations than that of either negative or neutral recommendations. The results of our study can effectively help service and product suppliers c作者: 冬眠 時間: 2025-3-22 17:26 作者: Delude 時間: 2025-3-22 23:39 作者: 寬敞 時間: 2025-3-23 02:41 作者: 原諒 時間: 2025-3-23 08:28
A Novel Linear Time Invariant Systems Order Reduction Approach Based on a Cooperative Multi-objectivng the same problems using various approaches and heuristic optimization tools and it is demonstrated that the set of solutions not only outperforms these approaches by the main criterion, but also provides good solutions with another criterion and a combination of them using the same computational 作者: BLANC 時間: 2025-3-23 11:47 作者: constitutional 時間: 2025-3-23 14:52 作者: cardiovascular 時間: 2025-3-23 21:29 作者: 充氣球 時間: 2025-3-24 01:48
,Introduction à l’optimisation de formes,parameters often depend on each optimization problem. However, it is difficult to decide the appropriate parameter setting for each problem in advance. In this study, the effect of parameter difference of the major crossover operators: Simulated Binary crossover (SBX), Differentioal Evolution operat作者: 并置 時間: 2025-3-24 04:02
Candace Walkington,Dawn M. Woods-objective chaotic evolution (MOCE). It extends the optimization application of chaotic evolution algorithm to multi-objective optimization field. The non-dominated sorting and tournament selection using crowding distance are two techniques to ensure Pareto dominance and solution diversity in EMO al作者: 座右銘 時間: 2025-3-24 07:29 作者: 準(zhǔn)則 時間: 2025-3-24 12:09 作者: forager 時間: 2025-3-24 18:27
https://doi.org/10.1007/978-3-030-80008-6nt comparison metrics on interval values and the associated offspring generations are critical. We first present a neighboring dominance metric for interval numbers comparisons. Then, the potential dominant solutions are predicted by constructing a directed graph with the neighboring dominance. We d作者: WITH 時間: 2025-3-24 20:37
Language and Rule of Law in Classical Athensquacy of an order reduction problem solution is estimated using two different criteria, but only one of them identifies the model. In this study, it was suggested to identify the parameters using both of the criteria, and since the criteria are complex and multi-extremum there is a need for a powerf作者: 不連貫 時間: 2025-3-25 00:31 作者: florid 時間: 2025-3-25 04:15 作者: onlooker 時間: 2025-3-25 09:46
Silvia Zorzetto,Francesco Ferrarorn and risk. We address the portfolio optimization problem with real-world constraints, where traditional optimization methods fail to efficiently find an optimal or near-optional solution. Hence, we design a modified cuckoo search (MCS) metaheuristic for finding good sub-optimal portfolios. Cuckoo 作者: Trypsin 時間: 2025-3-25 15:11
Dina Mendon?a,Florian Franken Figueiredo the computational ceiling when a large-scale network is dealt. The nature-inspired metaheuristic algorithm is a potential solver for optimizing a target function. Its parallel-computing architecture improves the computing efficiency for analyzing the large-scale network. This study proposes a novel作者: 放縱 時間: 2025-3-25 18:12 作者: prolate 時間: 2025-3-25 23:33 作者: GREG 時間: 2025-3-26 01:00
Conceptions of Giftedness and Talent an event, to understand how emotions affect subsequent product recommendations, in this study, we use the microblogging platform “Plurk” in conjunction with a Chinese emotional lexicon developed previously. More specifically, we identify emotional keywords as a basis for distinguishing user sentime作者: 煩擾 時間: 2025-3-26 07:43 作者: Systemic 時間: 2025-3-26 09:33
Conception of Justice: Pre-Axial India,the force field generated by each individual in a swarm is not exerting forces on the neighboring individuals but is being moved by the existence of the neighbors. Secondly, each individual is no longer considered as a particle but as a rigid-body with the ability to rotate with its force field. Thi作者: 預(yù)防注射 時間: 2025-3-26 15:09 作者: Prostatism 時間: 2025-3-26 17:05 作者: 訓(xùn)誡 時間: 2025-3-27 01:00 作者: 詩集 時間: 2025-3-27 03:00 作者: 大酒杯 時間: 2025-3-27 06:36 作者: Embolic-Stroke 時間: 2025-3-27 09:43
Using Multi-objective Evolutionary Algorithm to Solve Dynamic Environment and Economic Dispatch withdischarging behavior of EVs is dynamically managed in the premise of meeting the demands of system energy and user travel. In this paper, the nondominated sorting genetic algorithm-II (NSGA-II) is used to solve such a model.作者: Perigee 時間: 2025-3-27 15:21
Community Detection Under Exponential Random Graph Model: A Metaheuristic Approach swarm intelligence algorithm to detect communities. A new criterion, derived from the exponential random graph model with two communities, is proposed to detect the most significant community within the whole network. The feasibility and the detection accuracy of our algorithm are verified by the simulation studies.作者: OREX 時間: 2025-3-27 19:33 作者: CAMP 時間: 2025-3-28 01:02 作者: 營養(yǎng) 時間: 2025-3-28 02:27
Silvia Zorzetto,Francesco Ferraroearch space using Levy flights and allocates the good sub-optimal distribution of investment weights for a chosen set of assets. The MCS results show a clear improvement in comparison with previously published results, based on Markowitz and Sharpe models.作者: 盡責(zé) 時間: 2025-3-28 07:08
Psychoanalytic Critique and Beyond,terface with good interactivity. At the same time, an ALS recommendation algorithm based on Spark is proposed, and the performance and effect evaluation of the system are made in the virtual learning community.作者: 牢騷 時間: 2025-3-28 14:13 作者: CODA 時間: 2025-3-28 15:17 作者: Commemorate 時間: 2025-3-28 19:38
https://doi.org/10.1057/9780230611849 where the optimum dimension is unknown, the training algorithm must seek both positional and dimensional optima. The simulation results show that multi-dimensional Particle Swarm Optimization outperforms Genetic algorithm in training the effective multi-agent adaptive fuzzy neuronet for hourly solar irradiance forecasting.作者: Deject 時間: 2025-3-29 02:01 作者: 詢問 時間: 2025-3-29 05:11 作者: 反抗者 時間: 2025-3-29 09:23 作者: Urologist 時間: 2025-3-29 11:30 作者: myriad 時間: 2025-3-29 15:35 作者: HIKE 時間: 2025-3-29 21:34 作者: acheon 時間: 2025-3-30 00:30 作者: 雪上輕舟飛過 時間: 2025-3-30 04:20 作者: 火花 時間: 2025-3-30 10:05
Dina Mendon?a,Florian Franken Figueiredo swarm intelligence algorithm to detect communities. A new criterion, derived from the exponential random graph model with two communities, is proposed to detect the most significant community within the whole network. The feasibility and the detection accuracy of our algorithm are verified by the simulation studies.作者: 網(wǎng)絡(luò)添麻煩 時間: 2025-3-30 13:55
Critique, Dissent, Disciplinarity,hm improves the efficiency of PSO by recognizing inter-community edges based on .-inspired network model (PNM). Experiments in eight networks show that the proposed algorithm is effective and promising for community detection, compared with other algorithms.作者: Admire 時間: 2025-3-30 19:15
An Enhanced Particle Swarm Optimization Based on , Model for Community Detectionhm improves the efficiency of PSO by recognizing inter-community edges based on .-inspired network model (PNM). Experiments in eight networks show that the proposed algorithm is effective and promising for community detection, compared with other algorithms.作者: AVID 時間: 2025-3-30 22:54 作者: idiopathic 時間: 2025-3-31 01:50 作者: 掃興 時間: 2025-3-31 08:06
Non-dominated Sorting and Crowding Distance Based Multi-objective Chaotic Evolution-objective chaotic evolution (MOCE). It extends the optimization application of chaotic evolution algorithm to multi-objective optimization field. The non-dominated sorting and tournament selection using crowding distance are two techniques to ensure Pareto dominance and solution diversity in EMO al
