標(biāo)題: Titlebook: Artificial Evolution; 12th International C Stéphane Bonnevay,Pierrick Legrand,Marc Schoenauer Conference proceedings 2016 Springer Internat [打印本頁(yè)] 作者: TEMPO 時(shí)間: 2025-3-21 17:49
書目名稱Artificial Evolution影響因子(影響力)
書目名稱Artificial Evolution影響因子(影響力)學(xué)科排名
書目名稱Artificial Evolution網(wǎng)絡(luò)公開度
書目名稱Artificial Evolution網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Artificial Evolution被引頻次
書目名稱Artificial Evolution被引頻次學(xué)科排名
書目名稱Artificial Evolution年度引用
書目名稱Artificial Evolution年度引用學(xué)科排名
書目名稱Artificial Evolution讀者反饋
書目名稱Artificial Evolution讀者反饋學(xué)科排名
作者: 即席 時(shí)間: 2025-3-21 22:39
Reasoning, Judgement and Pragmaticsther combinatorial problems, local optima are not randomly distributed, instead they tend to be clustered around the global optimum. However, a recent study has observed that, for solutions close in evaluation to the global optimum, this structure breaks down into multiple valleys, forming what has 作者: 噱頭 時(shí)間: 2025-3-22 01:31
Reasoning, Judgement and Pragmaticsd A.S.H as representative algorithms of decomposition, indicators, and .-dominance based approaches for many-objective optimization. We use small MNK-landscapes to trace the dynamics of the algorithms generating high-resolution approximations of the Pareto optimal set. Also, we use large MNK-landsca作者: Monotonous 時(shí)間: 2025-3-22 06:31
Orna Peleg,Rachel Giora,Ofer Feinel simulator CMEM to analyze the evolutionary optimization of traffic signals minimizing travel time and fuel consumption on a real-world large scenario. We simulate the movement of 20.000 vehicles on the transport network of a 5.8 Km. area of Quito including 70 signal lights. Our aim is to clarify 作者: aqueduct 時(shí)間: 2025-3-22 10:35
Radiation-Induced Injury of the Liver,istic analysis can prove useful to a stochastic optimisation technique. GSA, that gathers information about the behaviour of functions receiving some inputs and delivering one or several outputs, is based on computationally-intensive stochastic sampling of a parameter space. Nevertheless, efficientl作者: 會(huì)議 時(shí)間: 2025-3-22 15:29 作者: VOK 時(shí)間: 2025-3-22 18:12
Use of Droplet PCR in Biomedical Research,e Differential Evolution, a small modification of Differential Evolution which aims at optimizing a small number of parameters (. one cluster) at the beginning, and incrementally increase the number of optimized parameters.作者: 護(hù)航艦 時(shí)間: 2025-3-22 23:49
Varsha Gupta,Baishnab Charan Tripathytaheuristic to be executed from a portfolio of available metaheuristics. Within the DAMS framework, we investigate different metaheuristic selection strategies which enable to choose locally at each time step a metaheuristic to execute. We conduct a throughout experimental analysis in order to bette作者: 未完成 時(shí)間: 2025-3-23 02:52 作者: cardiac-arrest 時(shí)間: 2025-3-23 07:02 作者: CIS 時(shí)間: 2025-3-23 13:04 作者: FAWN 時(shí)間: 2025-3-23 15:09 作者: 碎石 時(shí)間: 2025-3-23 19:57 作者: 陰郁 時(shí)間: 2025-3-24 01:02
Episodic Memory: Effortful Phenomena,ms of different classes. This system uses the metaphor of artificial life in which the artificial world represents the search space of a problem, populated by a set of feasible solutions of the problem and grouped into inanimate entities, called regions. Similarly, the world is inhabited by animated作者: 賠償 時(shí)間: 2025-3-24 05:29
Sensory Psychology and Perception,s functions that reward progress towards a desired objective or behavior. As a result, search increasingly focuses on higher-fitness areas. However, in problems with many local optima, such focus often leads to premature convergence that precludes reaching the intended objective. To remedy this prob作者: Spirometry 時(shí)間: 2025-3-24 09:37
Effects of Drugs on Reward Processes,on is widespread in insect societies and can appear in response to environmental heterogeneities or by attraction between individuals. Understanding this process requires linking individual behavioural rules of insects to a choice dynamics at the colony level. In this paper, we propose a model for t作者: 數(shù)量 時(shí)間: 2025-3-24 12:32 作者: incarcerate 時(shí)間: 2025-3-24 17:34
The Taguchi Approach to Quality Improvement,onclude that a precision . can be reached with cost . in dimension . within polylogarithmic factors for the sphere function. Compared to other (non comparison-based) algorithms, this rate is not excellent; on the other hand, it is classically considered that comparison-based algorithms have some rob作者: 規(guī)范要多 時(shí)間: 2025-3-24 21:29
Artificial Evolution978-3-319-31471-6Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: OFF 時(shí)間: 2025-3-25 00:11
Use of Droplet PCR in Biomedical Research,e Differential Evolution, a small modification of Differential Evolution which aims at optimizing a small number of parameters (. one cluster) at the beginning, and incrementally increase the number of optimized parameters.作者: AMOR 時(shí)間: 2025-3-25 05:38 作者: 油氈 時(shí)間: 2025-3-25 07:53 作者: 細(xì)頸瓶 時(shí)間: 2025-3-25 14:20 作者: burnish 時(shí)間: 2025-3-25 16:41
Conference proceedings 2016lowingtopics: Evolutionary Computation, Evolutionary Optimization, Co-evolution,Artificial Life, Population Dynamics, Theory, Algorithmics and Modeling,Implementations, Application of Evolutionary Paradigms to the Real World,Dynamic Optimization, Machine Learning and hybridization with other softcomputing techniques..作者: 柳樹；枯黃 時(shí)間: 2025-3-25 23:04
Orna Peleg,Rachel Giora,Ofer Feinthe nature and the extent of the conflict between these objectives. We also compare with a single-objective optimization algorithm where only travel time is optimized and evaluate the impact of the signals settings on gas emissions.作者: Notify 時(shí)間: 2025-3-26 02:52
Radiation-Induced Injury of the Liver,y exploiting information gathered from GSA might not be so straightforward. In this paper, we present three mono- and multi-objective counterexamples to prove how naively combining GSA and EA may mislead an optimisation process.作者: 有助于 時(shí)間: 2025-3-26 05:12 作者: Insatiable 時(shí)間: 2025-3-26 11:03 作者: 巧思 時(shí)間: 2025-3-26 16:00 作者: 憤慨點(diǎn)吧 時(shí)間: 2025-3-26 18:54 作者: 雪上輕舟飛過 時(shí)間: 2025-3-27 00:17
tions of other non-terminals, thereby increasing locality. The performance of the new representation is accessed on a set of benchmark problems. The results obtained confirm the effectiveness of the proposed approach, as it is able to outperform standard grammatical evolution on all selected optimization problems.作者: outskirts 時(shí)間: 2025-3-27 03:32 作者: Lymphocyte 時(shí)間: 2025-3-27 08:30
Approaches for Many-Objective Optimization: Analysis and Comparison on MNK-Landscapes,landscapes to trace the dynamics of the algorithms generating high-resolution approximations of the Pareto optimal set. Also, we use large MNK-landscapes to analyze their scalability to larger search spaces.作者: Infirm 時(shí)間: 2025-3-27 12:56
Quasi-random Numbers Improve the CMA-ES on the BBOB Testbed,ts provide a significant improvement in evolutionary optimization. In this paper, we experiment quasi-random mutations on a well known test case, namely the Coco/Bbob test case. We also include experiments on translated or rescaled versions of BBOB, on which we get similar improvements.作者: alcohol-abuse 時(shí)間: 2025-3-27 15:50 作者: geometrician 時(shí)間: 2025-3-27 17:58
A Distributed Hybrid Algorithm for the Graph Coloring Problem,ypes of perturbation moves are performed. All these search components are managed by a multi-agent model which uses reinforcement learning for decision making. The performance of the proposed algorithm is evaluated on well-known DIMACS benchmark instances.作者: Indigence 時(shí)間: 2025-3-27 22:29
Traffic Signal Optimization: Minimizing Travel Time and Fuel Consumption,the nature and the extent of the conflict between these objectives. We also compare with a single-objective optimization algorithm where only travel time is optimized and evaluate the impact of the signals settings on gas emissions.作者: Eulogy 時(shí)間: 2025-3-28 02:56
How to Mislead an Evolutionary Algorithm Using Global Sensitivity Analysis,y exploiting information gathered from GSA might not be so straightforward. In this paper, we present three mono- and multi-objective counterexamples to prove how naively combining GSA and EA may mislead an optimisation process.作者: Formidable 時(shí)間: 2025-3-28 08:21 作者: gorgeous 時(shí)間: 2025-3-28 12:24
0302-9743 nd Modeling,Implementations, Application of Evolutionary Paradigms to the Real World,Dynamic Optimization, Machine Learning and hybridization with other softcomputing techniques..978-3-319-31470-9978-3-319-31471-6Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 盲信者 時(shí)間: 2025-3-28 17:17
e performance. Our experiments also provide compelling evidence of the dynamic role of crossover during search: it is a useful operator across the whole search process. The idea of combining different type of operators in a distributed adaptive search model is worth further investigation.作者: champaign 時(shí)間: 2025-3-28 21:23 作者: 善變 時(shí)間: 2025-3-29 02:02 作者: CHECK 時(shí)間: 2025-3-29 04:42 作者: 元音 時(shí)間: 2025-3-29 10:45 作者: 補(bǔ)助 時(shí)間: 2025-3-29 15:11 作者: pulmonary 時(shí)間: 2025-3-29 17:00 作者: 消耗 時(shí)間: 2025-3-29 22:13
On the Codimension of the Set of Optima: Large Scale Optimisation with Few Relevant Variables,seless variables, thanks to a complexity bound . where . is the codimension of the set of optima, possibly .. In addition, experiments show that some evolutionary algorithms have a negligible computational complexity even in high dimension, making them practical for huge problems with many useless variables.作者: cutlery 時(shí)間: 2025-3-30 02:52 作者: 搖擺 時(shí)間: 2025-3-30 05:34
Effects of Drugs on Reward Processes,ction among individuals, can be used by the group of agent to select collectively an aggregation site among two identical or different shelters by estimating the size of each shelter during the collective decision-making process.作者: misanthrope 時(shí)間: 2025-3-30 09:13 作者: 積云 時(shí)間: 2025-3-30 16:02 作者: Needlework 時(shí)間: 2025-3-30 19:52
Conference proceedings 2016n Lyon, France, in October 2015...The 18 revised papers were carefully reviewed andselected from 31 submissions. The focus of the conference is on followingtopics: Evolutionary Computation, Evolutionary Optimization, Co-evolution,Artificial Life, Population Dynamics, Theory, Algorithmics and Modelin作者: Incise 時(shí)間: 2025-3-31 00:23 作者: fringe 時(shí)間: 2025-3-31 03:30 作者: brother 時(shí)間: 2025-3-31 08:48 作者: Ingest 時(shí)間: 2025-3-31 09:18
Variance Reduction in Population-Based Optimization: Application to Unit Commitment,作者: 物質(zhì) 時(shí)間: 2025-3-31 13:49
Stéphane Bonnevay,Pierrick Legrand,Marc Schoenauer作者: lethal 時(shí)間: 2025-3-31 21:31 作者: phytochemicals 時(shí)間: 2025-3-31 22:48
Effects of Cooperation in a Bioinspired Multi-agent Autonomous System for Solving Optimization Prob is usually used as benchmark for continuous optimization methods and the knapsack problem. The preliminary results thus obtained show that the dynamics of the implemented model is most effective when there is cooperation between the agents, due to the learning process that occurs from the actions a作者: Inertia 時(shí)間: 2025-4-1 01:57
Novelty-Driven Particle Swarm Optimization,olving tasks in genetic programming, this paper implements NdPSO as an extension of the grammatical swarm method, which combines PSO with genetic programming. The resulting NdPSO implementation is tested in three different domains representative of those in which it might provide advantage over obje作者: judicial 時(shí)間: 2025-4-1 10:01
The Multi-Funnel Structure of TSP Fitness Landscapes: A Visual Exploration,ther combinatorial problems, local optima are not randomly distributed, instead they tend to be clustered around the global optimum. However, a recent study has observed that, for solutions close in evaluation to the global optimum, this structure breaks down into multiple valleys, forming what has 作者: 啜泣 時(shí)間: 2025-4-1 12:10
Approaches for Many-Objective Optimization: Analysis and Comparison on MNK-Landscapes,d A.S.H as representative algorithms of decomposition, indicators, and .-dominance based approaches for many-objective optimization. We use small MNK-landscapes to trace the dynamics of the algorithms generating high-resolution approximations of the Pareto optimal set. Also, we use large MNK-landsca作者: 事物的方面 時(shí)間: 2025-4-1 15:05
Traffic Signal Optimization: Minimizing Travel Time and Fuel Consumption,el simulator CMEM to analyze the evolutionary optimization of traffic signals minimizing travel time and fuel consumption on a real-world large scenario. We simulate the movement of 20.000 vehicles on the transport network of a 5.8 Km. area of Quito including 70 signal lights. Our aim is to clarify 作者: PRISE 時(shí)間: 2025-4-1 21:48 作者: 母豬 時(shí)間: 2025-4-2 01:59 作者: 矛盾 時(shí)間: 2025-4-2 04:49
