Tri-objective parallel machine with job splitting and sequence dependent setup times using differential evolution and particle swarm optimization by Warisa Wisittipanich, Nuttachat Wisittipanit

“…This study applied two metaheuristic algorithms, namely differential evolution (DE) and particle swarm optimization (PSO) to the tri-objective PMSP with job splitting and sequence dependent setup times (PMSP-JSSDST) in order to obtain solutions with simultaneously minimized makespan, tardiness and total energy consumption. …”
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A novel extraction model optimization with effective separation coefficient for rare earth extraction process using improve differential evolution by Fangping Xu, Hui Yang, Jianyong Zhu, Wenjia Chang

“…Taking into account the multi-modal and multi-variable characteristics of the optimized objective function, we put forth an enhanced version of the improved differential evolution algorithm, the Linear-Chaos and Two Mutation Strategies of Adaptive Differential Evolution (LCTADE)with Covariance Matrix and Cauchy Perturbation(CC-LCTADE). …”
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Improvement of YOLO v8 Segmentation Algorithm and Its Study in the Identification of Hazards in Plateau Pika by Yaosheng Han, Yunpeng Jin, Chunmei Li, Xiangjie Huang

“…Secondly, the latest segmentation algorithm provided by YOLO v8 is improved to design a segmentation algorithm that can accurately detect the distribution of rodent infestation in the plateau scene. …”
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A combined model of shoot phosphorus uptake based on sparse data and active learning algorithm by Tianli Wang, Yi Zhang, Haiyan Liu, Fei Li, Dayong Guo, Ning Cao, Yubin Zhang

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Using Relational Biology with Loop Analysis to Study the North Atlantic Biological Carbon Pump in a ‘Hybrid’ Non-Algorithmic Manner by Patricia A. Lane

“…It has been challenging, however, to incorporate his theory to develop a fully non-algorithmic methodology that retains the essence of his thinking while creating more operational models of living systems that can be used to explore other facets of life and answer different questions. …”
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Individual tree segmentation of airborne and UAV LiDAR point clouds based on the watershed and optimized connection center evolution clustering by Yi Li, Donghui Xie, Yingjie Wang, Shuangna Jin, Kun Zhou, Zhixiang Zhang, Weihua Li, Wuming Zhang, Xihan Mu, Guangjian Yan

“…Here, we propose a new individual tree segmentation method, which couples the classical and efficient watershed algorithm (WS) and the newly developed connection center evolution (CCE) clustering algorithm in pattern recognition. …”
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Spatiotemporal evolution of 1998 extreme flood event in the Yangtze River basin from the perspective of the reconstructed GRACE/GRACE-FO data by Lilu Cui, Jiacheng Meng, Bo Zhong, Jiachun An, Yu Li, Haoyang Guo, Yuheng Lu

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Assessing glacier thickness changes with multi-temporal UAV-derived DEMs: The evolution of Forni Glacier over the period 2014–2022 by Valeria Belloni, Davide Fugazza, Kevin Hanson, Marco Scaioni, Martina Di Rita

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Elitism-based multi-objective differential evolution with extreme learning machine for feature selection: a novel searching technique by Subrat Kumar Nayak, Pravat Kumar Rout, Alok Kumar Jagadev, Tripti Swarnkar

“…This paper presents an Elitism-based Multi-objective Differential Evolution algorithm for FS and the novelty lies in the searching process which uses Minkowski Score (MS) and simultaneously optimises three objectives. …”
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Classification of schizophrenia, bipolar disorder and major depressive disorder with comorbid traits and deep learning algorithms by Xiangning Chen, Yimei Lu, Joan Manuel Cue, Mira V. Han, Vishwajit L. Nimgaonkar, Daniel R. Weinberger, Shizhong Han, Zhongming Zhao, Jingchun Chen

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Moanna: Multi-Omics Autoencoder-Based Neural Network Algorithm for Predicting Breast Cancer Subtypes by Richard Lupat, Rashindrie Perera, Sherene Loi, Jason Li

“…Here, we propose a novel deep-learning-based algorithm, Moanna, that is trained to integrate multi-omics data for predicting breast cancer subtypes. …”
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Differentiation of multiple adrenal adenoma subtypes based on a radiomics and clinico-radiological model: a dual-center study by Xinzhang Zhang, Yapeng Si, Xin Shi, Yiwen Zhang, Liuyang Yang, Junfeng Yang, Ye Zhang, Jinjun Leng, Pingping Hu, Hao Liu, Jiaqi Chen, Wenliang Li, Wei Song, Jianping Zhu, Maolin Yang, Wei Li, Junfeng Wang

“…The available methods for adrenal function evaluation are invasive and costly. Moreover, their accuracy is influenced by numerous factors. …”
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Preliminary exploratory study on differential diagnosis between benign and malignant peripheral lung tumors: based on deep learning networks by Yuan Wang, Yuan Wang, Yutong Zhang, Yongxin Li, Tianyu She, Meiqing He, Hailing He, Dong Zhang, Dong Zhang, Jue Jiang

“…The dataset was divided into a training set (n = 296) and a test set (n = 75) in an 8:2 ratio for further analysis and model evaluation. Five distinct deep learning models were developed using ResNet152, ResNet101, ResNet50, ResNet34, and ResNet18 algorithms. …”
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Image encryption using dna-sequences, chaotic dynamics and hash fuctions by A. V. Sidorenko, M. S. Shishko

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Induction of Convolutional Decision Trees for Semantic Segmentation of Color Images Using Differential Evolution and Time and Memory Reduction Techniques by Adriana-Laura López-Lobato, Héctor-Gabriel Acosta-Mesa, Efrén Mezura-Montes

“…However, they have primarily been focused on analyzing grayscale images due to the computational cost of the Differential Evolution (DE) algorithm, which is employed in these techniques. …”
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Scenario-Based Association Rule Mining in Veterinary Services Using FP-Growth: Differentiating Clinical and Customer-Driven Patterns by Rafi Dio, Aulia Agung Dermawan, Dwila Sempi Yusiani, Rifaldi Herikson, Andikha Andikha, Dwi Ely Kurniawan, Adyk Marga Raharja

“…This study aims to differentiate between procedural and customer-driven service patterns by applying the FP-Growth association rule mining algorithm to 1,000 anonymized transactions comprising 94 unique items, collected from a veterinary clinic in West Java, Indonesia, during 2023. …”
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Alteration in EEG Delta and Beta Power During Working Memory Performance Differentiates Patients with Parkinson’s Disease with and without Dementia by Anita Pal, Madhuri Behari, Ratna Sharma

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Creep Parameter Inversion and Long-Term Stability Analysis of Tunnel Based on GP-DE Intelligent Algorithm by Fengrui Zhang, Annan Jiang, Xinping Guo, Xiurong Yang

“…To obtain the creep parameters accurately, considering the advantages of Gauss process and differential evolution algorithm, coupling the two methods, a Gauss process-differential evolution intelligent inversion method is proposed. …”
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A Multi-Criteria Perceptual Visual Complexity Metrics-Based Optimization Approach to User Interface Design Layouts by Eren Akca, Omer Ozgur Tanriover, Asim Egemen Yilmaz

“…To this aim, we developed a method that relies on perceptual visual complexity metrics specifically, alignment, balance, density and an introduced measure called distance to focal area. Differential evolution algorithm is adapted to the problem to generate a set of pareto optimal alternative layout designs. …”
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CECT-Based Radiomic Nomogram of Different Machine Learning Models for Differentiating Malignant and Benign Solid-Containing Renal Masses by Qian L, Fu B, He H, Liu S, Lu R

“…Four mainstream machine learning algorithm training models, namely, support vector machine (SVM), k-nearest neighbour (kNN), light gradient boosting (LightGBM) and logistic regression (LR), were constructed to determine the best classifier model. …”
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