標(biāo)題: Titlebook: Applications of Evolutionary Computation; 23rd European Confer Pedro A. Castillo,Juan Luis Jiménez Laredo,Francis Conference proceedings 20 [打印本頁(yè)] 作者: ossicles 時(shí)間: 2025-3-21 17:46
書目名稱Applications of Evolutionary Computation影響因子(影響力)
書目名稱Applications of Evolutionary Computation影響因子(影響力)學(xué)科排名
書目名稱Applications of Evolutionary Computation網(wǎng)絡(luò)公開(kāi)度
書目名稱Applications of Evolutionary Computation網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書目名稱Applications of Evolutionary Computation被引頻次
書目名稱Applications of Evolutionary Computation被引頻次學(xué)科排名
書目名稱Applications of Evolutionary Computation年度引用
書目名稱Applications of Evolutionary Computation年度引用學(xué)科排名
書目名稱Applications of Evolutionary Computation讀者反饋
書目名稱Applications of Evolutionary Computation讀者反饋學(xué)科排名
作者: –scent 時(shí)間: 2025-3-21 21:51 作者: recede 時(shí)間: 2025-3-22 03:19
Joshua D. Reuther,Ben A. Pottertors. In its original definition Pattern Search moves along the directions of each variable. Amongst its advantages, the algorithm does not require any knowledge of derivatives or analytical expression of the function to optimise. However, the performance of Pattern Search is heavily problem depende作者: meditation 時(shí)間: 2025-3-22 08:20 作者: 嬉耍 時(shí)間: 2025-3-22 08:47 作者: 螢火蟲 時(shí)間: 2025-3-22 13:52
William H. Casey,C. André Ohlin events are allowed and which ones should be forbidden. In this work we propose a way to automatically obtain rules that generalise these single-event based rules using Genetic Programming (GP), which, besides, should be able to present them in an understandable way. Our GP-based system obtains good作者: 松雞 時(shí)間: 2025-3-22 19:50
Encyclopedia of Earth Sciences Seriesetworks (LONs) that model the global structure of search spaces, STNs model the search trajectories of algorithms. Unlike LONs, the nodes of the network are not restricted to local optima but instead represent a given state of the search process. Edges represent search progression between consecutiv作者: Jubilation 時(shí)間: 2025-3-23 00:42
Dennis Odijk,Peter J. G. Teunissenogies by crossover and mutation. Within this system we compare two approaches to creating good controllers, i.e., evolution only and evolution plus learning. In the first one the controller of a robot child is inherited, so that it is produced by applying crossover and mutation to the controllers of作者: Spartan 時(shí)間: 2025-3-23 05:14
Alfvén, Hannes Olof G?sta (1908–1995) aspect that affects the safety and efficiency of urban traffic is the configuration of traffic lights and junctions. Here, we propose a general framework, based on a realistic urban traffic simulator, SUMO, to aid city planners to optimize traffic lights, based on a customized version of NSGA-II. W作者: ITCH 時(shí)間: 2025-3-23 06:42 作者: 直覺(jué)好 時(shí)間: 2025-3-23 11:07
Acceptance and Commitment Therapyon of dynamical systems which is based on matrix multiplication. That is similar to how an artificial neural network (ANN) is represented in a deep learning library and its computation can be faster because of the optimized matrix operations that such type of libraries have. Initially, we implement 作者: bypass 時(shí)間: 2025-3-23 17:13 作者: 深淵 時(shí)間: 2025-3-23 21:40 作者: 移動(dòng) 時(shí)間: 2025-3-24 00:30
David T. Albee,Meredith Rucker Hunteric or behaviour analysis of ransomware, hence known as behaviour-based detection models. A big challenge in automated behaviour-based ransomware detection and classification is high dimensional data with numerous features distributed into various groups. Feature selection algorithms usually help to 作者: prediabetes 時(shí)間: 2025-3-24 04:51
https://doi.org/10.1007/978-3-030-22009-9lobal optima. The proposed complexity method provides a partial answer to this question in the form of the estimated sample size needed to sample all basins of attraction of all global optima at least once. The rationale behind the approach is that, in optimization, in order to locate all possible o作者: Folklore 時(shí)間: 2025-3-24 07:40 作者: 沉著 時(shí)間: 2025-3-24 12:34
Acceptance and Commitment Therapyf such variables make them statically indeterminate, meaning that a change in one design variable affects the response of the entire structure. This property makes the design of cable-stayed bridges a complex optimization problem. In this work, we use a Genetic Algorithm to evolve solutions for this作者: FRAX-tool 時(shí)間: 2025-3-24 17:45
H?kan J?nson,Annika Taghizadeh Larssoniverse performance requirements on a common substrate platform. Of particular interest among different facets of network slicing is the problem of designing an individual network slice tailored specifically to match the requirements of the big-bandwidth next generation network services. In this work作者: FLUSH 時(shí)間: 2025-3-24 22:57 作者: CRACK 時(shí)間: 2025-3-24 23:45
Accessible or Adaptable Housingdule, different robotic structures with better performance for a given task can be found. In this paper, we modify the modules of a modular robot platform, the EMERGE modular robot, in two different ways: changing the length of the module and changing the shape of the starting module (base). We use 作者: 擦試不掉 時(shí)間: 2025-3-25 05:04 作者: objection 時(shí)間: 2025-3-25 09:10
978-3-030-43721-3Springer Nature Switzerland AG 2020作者: MEET 時(shí)間: 2025-3-25 14:34
0302-9743 games, applications of deep-bioinspired algorithms, parallel and distributed systems, and evolutionary machine learning.?.978-3-030-43721-3978-3-030-43722-0Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: ADOPT 時(shí)間: 2025-3-25 16:47 作者: 盤旋 時(shí)間: 2025-3-25 22:02 作者: 遠(yuǎn)地點(diǎn) 時(shí)間: 2025-3-26 00:31
Acceptance and Commitment Therapye between convergence and diversity for multi- and many-objective optimization problems. Our experimental results demonstrate that the proposed algorithm is efficient and reliable for dealing with different normalized and scaled problems, outperforming several other state-of-the-art multi- and many-objective evolutionary algorithms.作者: 陶醉 時(shí)間: 2025-3-26 07:43 作者: Defraud 時(shí)間: 2025-3-26 09:22 作者: Lignans 時(shí)間: 2025-3-26 13:52 作者: hedonic 時(shí)間: 2025-3-26 19:33
EvoCluster: An Open-Source Nature-Inspired Optimization Clustering Framework in Python sets. The current implementation of the framework includes ten metaheristic optimizers, thirty datasets, five objective functions, and twelve evaluation measures. The source code of EvoCluster is publicly available at (.).作者: Aboveboard 時(shí)間: 2025-3-26 21:02
A Decomposition-Based Evolutionary Algorithm with Adaptive Weight Vectors for Multi- and Many-objecte between convergence and diversity for multi- and many-objective optimization problems. Our experimental results demonstrate that the proposed algorithm is efficient and reliable for dealing with different normalized and scaled problems, outperforming several other state-of-the-art multi- and many-objective evolutionary algorithms.作者: intelligible 時(shí)間: 2025-3-27 02:26 作者: 吸氣 時(shí)間: 2025-3-27 07:32
What Is Your MOVE: Modeling Adversarial Network Environmentsetwork topology and possible applications in the network. The results show that the evolved strategies far surpass randomly generated strategies. Finally, the evolved strategies can help us to reach some more general conclusions for both attacker and defender sides.作者: Awning 時(shí)間: 2025-3-27 09:57 作者: IOTA 時(shí)間: 2025-3-27 15:09 作者: 綠州 時(shí)間: 2025-3-27 19:40
Barry R. Bickmore,Matthew C. F. Wandered up the solving process for four common variants of the electric vehicle charging scheduling problem. Based on the results, the most important solver parameters are identified. It is shown that by tuning a very limited number of parameters, speed-ups of 60% and more can be achieved.作者: 起草 時(shí)間: 2025-3-28 01:38
Encyclopedia of Earth Sciences Seriestwo well-known population-based algorithms: particle swarm optimisation and differential evolution when applied to benchmark continuous optimisation problems. We also offer a comparative visual analysis of the search dynamics in terms of merged search trajectory networks.作者: 分開(kāi)如此和諧 時(shí)間: 2025-3-28 04:25
Dennis Odijk,Peter J. G. Teunissenshow that the learning approach does not only lead to different fitness levels, but also to different (bigger) robots. This constitutes a quantitative demonstration that changes in brains, i.e., controllers, can induce changes in the bodies, i.e., morphologies.作者: GONG 時(shí)間: 2025-3-28 07:23 作者: florid 時(shí)間: 2025-3-28 13:34 作者: 令人苦惱 時(shí)間: 2025-3-28 17:45 作者: 狂亂 時(shí)間: 2025-3-28 19:23
Evolving-Controllers Versus Learning-Controllers for Morphologically Evolvable Robotsshow that the learning approach does not only lead to different fitness levels, but also to different (bigger) robots. This constitutes a quantitative demonstration that changes in brains, i.e., controllers, can induce changes in the bodies, i.e., morphologies.作者: 終端 時(shí)間: 2025-3-28 23:55
Simulation-Driven Multi-objective Evolution for Traffic Light Optimization-objective fashion to obtain a number of Pareto-optimal light configurations. Our experiments, conducted on two city scenarios in Italy and different combinations of fitness functions, demonstrate the validity of this approach and show how evolutionary optimization is an effective tool for traffic light optimization.作者: nullify 時(shí)間: 2025-3-29 05:19
Automatic Rule Extraction from Access Rules Using Genetic Programming dataset coverage and small ratios of false positives and negatives in the simulation results over real data, after testing different fitness functions and configurations in the way of coding the individuals.作者: conduct 時(shí)間: 2025-3-29 07:13 作者: consolidate 時(shí)間: 2025-3-29 11:24
William H. Casey,C. André Ohlin dataset coverage and small ratios of false positives and negatives in the simulation results over real data, after testing different fitness functions and configurations in the way of coding the individuals.作者: iodides 時(shí)間: 2025-3-29 19:02
A Local Search for Numerical Optimisation Based on Covariance Matrix Diagonalisationtors. In its original definition Pattern Search moves along the directions of each variable. Amongst its advantages, the algorithm does not require any knowledge of derivatives or analytical expression of the function to optimise. However, the performance of Pattern Search is heavily problem depende作者: BLAZE 時(shí)間: 2025-3-29 20:07 作者: 倫理學(xué) 時(shí)間: 2025-3-30 02:27
Optimizing the Hyperparameters of a Mixed Integer Linear Programming Solver to Speed up Electric Vehhe optimization can represent an issue for the practical use. However, by tuning the parameter setting of the employed solver, it is possible to speed up the optimization process. The present work evaluates two popular hyperparameter tuning tools – irace (iterated racing) and SMAC (sequential model-作者: 外向者 時(shí)間: 2025-3-30 06:55 作者: microscopic 時(shí)間: 2025-3-30 08:42
Search Trajectory Networks of Population-Based Algorithms in Continuous Spacesetworks (LONs) that model the global structure of search spaces, STNs model the search trajectories of algorithms. Unlike LONs, the nodes of the network are not restricted to local optima but instead represent a given state of the search process. Edges represent search progression between consecutiv作者: CLIFF 時(shí)間: 2025-3-30 14:40 作者: PLAYS 時(shí)間: 2025-3-30 19:22
Simulation-Driven Multi-objective Evolution for Traffic Light Optimization aspect that affects the safety and efficiency of urban traffic is the configuration of traffic lights and junctions. Here, we propose a general framework, based on a realistic urban traffic simulator, SUMO, to aid city planners to optimize traffic lights, based on a customized version of NSGA-II. W作者: 翻布尋找 時(shí)間: 2025-3-31 00:12 作者: 巨碩 時(shí)間: 2025-3-31 01:04
EvoDynamic: A Framework for the Evolution of Generally Represented Dynamical Systems and Its Applicaon of dynamical systems which is based on matrix multiplication. That is similar to how an artificial neural network (ANN) is represented in a deep learning library and its computation can be faster because of the optimized matrix operations that such type of libraries have. Initially, we implement 作者: 容易懂得 時(shí)間: 2025-3-31 06:45
A Decomposition-Based Evolutionary Algorithm with Adaptive Weight Vectors for Multi- and Many-objecttimization. Numerous MOEA/D variants are focused on solving the normalized multi- and many-objective problems without paying attention to problems having objectives with different scales. For this purpose, this paper proposes a decomposition-based evolutionary algorithm with adaptive weight vectors 作者: 亂砍 時(shí)間: 2025-3-31 10:24
Differential Evolution Multi-Objective for Tertiary Protein Structure Predictionms, the protein structure prediction is a NP-Hard problem?[.], meaning that there is no efficient algorithm that can find a solution in a viable computational time. Nonetheless, the energy terms that compose different force fields seem to be conflicting among themselves, leading to a multi-objective作者: motivate 時(shí)間: 2025-3-31 14:29
Particle Swarm Optimization: A Wrapper-Based Feature Selection Method for Ransomware Detection and Cic or behaviour analysis of ransomware, hence known as behaviour-based detection models. A big challenge in automated behaviour-based ransomware detection and classification is high dimensional data with numerous features distributed into various groups. Feature selection algorithms usually help to 作者: 致敬 時(shí)間: 2025-3-31 18:30 作者: Projection 時(shí)間: 2025-3-31 21:42 作者: 射手座 時(shí)間: 2025-4-1 04:16
Designing Cable-Stayed Bridges with?Genetic Algorithmsf such variables make them statically indeterminate, meaning that a change in one design variable affects the response of the entire structure. This property makes the design of cable-stayed bridges a complex optimization problem. In this work, we use a Genetic Algorithm to evolve solutions for this作者: genuine 時(shí)間: 2025-4-1 07:38
A Fast, Scalable Meta-Heuristic for?Network Slicing Under Traffic Uncertaintyiverse performance requirements on a common substrate platform. Of particular interest among different facets of network slicing is the problem of designing an individual network slice tailored specifically to match the requirements of the big-bandwidth next generation network services. In this work
