An Improved Human Evolution Optimization Algorithm for Unmanned Aerial Vehicle 3D Trajectory Planning by Xue Wang, Shiyuan Zhou, Zijia Wang, Xiaoyun Xia, Yaolong Duan

“…Second, recognizing the sensitivity of population diversity to Logistic Chaotic Mapping in a traditional Human Evolution Optimization Algorithm (HEOA), an opposition-based learning strategy is employed to uniformly initialize the population distribution, thereby enhancing the algorithm’s global optimization capability. …”
Get full text

Harmony Search Based Parameter Ensemble Adaptation for Differential Evolution by Rammohan Mallipeddi

“…In differential evolution (DE) algorithm, depending on the characteristics of the problem at hand and the available computational resources, different strategies combined with a different set of parameters may be effective. …”
Get full text

An Actor–Critic-Based Hyper-Heuristic Autonomous Task Planning Algorithm for Supporting Spacecraft Adaptive Space Scientific Exploration by Junwei Zhang, Liangqing Lyu

“…Based on this requirement, this paper proposes an actor–critic-based hyper-heuristic autonomous mission planning algorithm, which is used for mission planning and execution at different levels to support spacecraft Adaptive Space Scientific Exploration in deep space environments. …”
Get full text

Optimizing adaptive modulation technique using standard propagation model for enhanced wireless communication channels by Rahim Khan, Zahid Ullah Khan, Sher Taj, Sajid Ullah Khan, Javed Khan, Nazik Alturki, Sultan Alanazi

Get full text

Differential Evolution with Novel Mutation and Adaptive Crossover Strategies for Solving Large Scale Global Optimization Problems by Ali Wagdy Mohamed, Abdulaziz S. Almazyad

“…This paper presents Differential Evolution algorithm for solving high-dimensional optimization problems over continuous space. …”
Get full text

Improved Parallel Differential Evolution Algorithm with Small Population for Multi-Period Optimal Dispatch Problem of Microgrids by Tianle Li, Yifei Li, Fang Wang, Cheng Gong, Jingrui Zhang, Hao Ma

“…In the new approach, the main population of the parallel algorithm is divided into several small populations, and each performs the original operators of a differential evolution algorithm, i.e., mutation, crossover, and selection, in different processes concurrently. …”
Get full text

A two phase differential evolution algorithm with perturbation and covariance matrix for PEMFC parameter estimation challenges by Mohammad Aljaidi, Pradeep Jangir, Arpita, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, G. Gulothungan, Ali Fayez Alkoradees, Mohammad Khishe

“…In this study, a novel algorithm PCM-DE, based on the Differential Evolution framework, is proposed. …”
Get full text

Parameter Identification in Triple-Diode Photovoltaic Modules Using Hybrid Optimization Algorithms by Dhiaa Halboot Muhsen, Haider Tarish Haider, Yaarob Al-Nidawi

“…Seven different experimental data sets are used to improve the performance of the proposed differential evolution with an integrated mutation per iteration algorithm (DEIMA). …”
Get full text

Comprehensive influence evaluation algorithm of complex network nodes based on global-local attributes by Weijin JIANG, Ying YANG, Tiantian LUO, Wenying ZHOU, En LI, Xiaowei ZHANG

“…Mining key nodes in the network plays a great role in the evolution of information dissemination, virus marketing, and public opinion control, etc.The identification of key nodes can effectively help to control network attacks, detect financial risks, suppress the spread of viruses diseases and rumors, and prevent terrorist attacks.In order to break through the limitations of existing node influence assessment methods with high algorithmic complexity and low accuracy, as well as one-sided perspective of assessing the intrinsic action mechanism of evaluation metrics, a comprehensive influence (CI) assessment algorithm for identifying critical nodes was proposed, which simultaneously processes the local and global topology of the network to perform node importance.The global attributes in the algorithm consider the information entropy of neighboring nodes and the shortest distance nodes between nodes to represent the local attributes of nodes, and the weight ratio of global and local attributes was adjusted by a parameter.By using the SIR (susceptible infected recovered) model and Kendall correlation coefficient as evaluation criteria, experimental analysis on real-world networks of different scales shows that the proposed method is superior to some well-known heuristic algorithms such as betweenness centrality (BC), closeness centrality (CC), gravity index centrality(GIC), and global structure model (GSM), and has better ranking monotonicity, more stable metric results, more adaptable to network topologies, and is applicable to most of the real networks with different structure of real networks.…”
Get full text

AUV path planning method based on improved sparrow search algorithm by Lijun TANG, Yunxia FAN, Xingyu ZHOU, Qian SUN

“…By modeling the uncertain ocean currents as intervals, the algorithm can accurately calculate the energy consumption and navigation times for different paths. …”
Get full text

An Industrial Internet Security Assessment Model Based on a Selectable Confidence Rule Base by Qingqing Yang, Shiming Li, Yuhe Wang, Guoxing Li, Yanbin Yuan

“…Then, in combination with the Selection covariance matrix adaptive evolution strategy (S-CMA-ES) algorithm, a parameter optimization method for the BRB-s model is designed, which expands the selective constraints on expert knowledge. …”
Get full text

Research on Optimized Algorithm for Deep Learning Based Recognition of Sediment Particles in Turbulent Flow by WANG Hao, YANG Feiqi, ZHANG Lei, WU Wei, XIE Haonan, ZHAO Lin

“…The YOLOv5 (you only look once) method is designed to rapidly and accurately detect specific target objects and their locations in images after training on a sampled dataset. The YOLOv5 algorithm adopted in this study excels at detecting small targets and provides multi-scale detection, strong versatility, fast training, inference speeds, and adaptable fine-tuning capabilities. …”
Get full text

Global progress in competitive co-evolution: a systematic comparison of alternative methods by Stefano Nolfi, Paolo Pagliuca

“…The usage of broad sets of training data is paramount to evolve adaptive agents. In this respect, competitive co-evolution is a widespread technique in which the coexistence of different learning agents fosters adaptation, which in turn makes agents experience continuously varying environmental conditions. …”
Get full text

State information-driven surrogate-assisted differential evolution for computationally expensive constrained optimization problems by Zihua Zhu, Zan Yang, Zhiyong Liu, Liming Chen, Xiwen Cai

“…Abstract In this paper, a state information-driven surrogate-assisted differential evolution called SI-SADE is proposed for solving expensive constrained optimization problems, in which both the population state and adaptive search mechanism are respectively evaluated and designed based on the feasibility and state information. …”
Get full text

Evaluation and comparison of methods for neuronal parameter optimization using the Neuroptimus software framework. by Máté Mohácsi, Márk Patrik Török, Sára Sáray, Luca Tar, Gábor Farkas, Szabolcs Káli

Get full text

RLDEAO optimized of air quality data clustering analysis(RLDEAO优化的空气质量数据聚类分析) by 田闯(TIAN Chuang), 黄鹤(HUANG He), 杨澜(YANG Lan), 王会峰(WANG Huifeng), 茹锋(RU Feng)

“…In view of this deficiency, we propose the adaptive dimension-by-dimension keyhole imaging reverse learning strategy, Levy flight combined with stagnation perturbation strategy and mutation evolution of the survival of the fittest to improve the search performance of the algorithm, thus avoiding local optimization; Secondly, a weighted maximum minimum distance product (WMMP) is designed to calculate the cluster center point, which can reflect the importance of each feature in the data and play a good role to improve the clustering results; Finally, RLDEAO and WMMP are combined to optimize K-means complementary iteration. …”
Get full text

An Interpretable Method for Asphalt Pavement Skid Resistance Performance Evaluation Under Sand-Accumulated Conditions Based on Multi-Scale Fractals by Yuhan Weng, Zhaoyun Sun, Huiying Liu, Yingbin Gu

Get full text

Efficient control strategy for electric furnace temperature regulation using quadratic interpolation optimization by Serdar Ekinci, Davut Izci, Veysel Gider, Laith Abualigah, Mohit Bajaj, Ievgen Zaitsev

“…To ensure optimal performance, the parameters of the RPIDD2 controller are optimized using metaheuristic algorithms, including the flood optimization algorithm (FLA), reptile search algorithm (RSA), particle swarm optimization (PSO) and differential evolution (DE). …”
Get full text

A Comparison of Inversion Methods for Surrogate‐Based Groundwater Contamination Source Identification With Varying Degrees of Model Complexity by Zhenbo Chang, Zhilin Guo, Kewei Chen, Zibo Wang, Yang Zhan, Wenxi Lu, Chunmiao Zheng

“…Each method has its own advantages and disadvantages under specific site conditions. To evaluate the applicability of these methods, we chose one representative inversion algorithm from each category, namely the Improved Butterfly Optimization Algorithm (IBOA) for simulation optimization, the Ensemble Smoother with Multiple Data Assimilation (ES‐MDA) for data assimilation, and the DiffeRential Evolution Adaptive Metropolis with a Snooker Update and Sampling from a Past Archive (DREAM(ZS)) for Bayesian inference. …”
Get full text

Research on Stacking Distribution of Steel Plates Input Based on Improved Multi-objective Particle Swarm Optimization by ZHONG Chuanjie, CHENG Wenming, DU Run, GAO Xuchao, ZHANG Lin

“…However, the difference was slight. Since the output of the multi-objective algorithm was a Pareto solution set, four indices, uniformity, convergence, diversity, and dominance, were selected to evaluate the distribution in the solution space and to compare the solution results of each algorithm. …”
Get full text