Artificial Neural Network Approach to Study Imprecisely Defined Nonlinear Systems With Case Studies by Lakshmi Durga Pathipati, Sukanta Nayak

“…A feed-forward neural network (FFNN) is used to generate outputs based on initial guesses for the field variables, and the ANN-LM algorithm optimizes the solution by minimizing the error between predicted and target values. …”
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Spatiotemporal Land Use Change Detection Through Automated Sampling and Multi-Feature Composite Analysis: A Case Study of the Ebinur Lake Basin by Yi Yang, Liang Zhao, Ya Guo, Shihua Liu, Xiang Qin, Yixiao Li, Xiaoqiong Jiang

“…This study proposes an innovative technical framework that integrates automated sample generation, multi-feature optimization, and classification model refinement to enhance the accuracy of land use classification and enable detailed spatiotemporal analysis in the Ebinur Lake Basin. …”
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Optimal Model-Free Mean-Square Consensus for Multi-Agents with Markov Switching Topology by Ruoxun Ma, Lipo Mo, Bokang Zhou

“…A performance function for each agent under switching topologies is established and a policy iteration algorithm using system data is proposed based on the Bellman optimality principle. The theoretical analysis shows that the consensus error realizes mean-square consensus and the performance function is optimized. …”
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Finding Reliability of Slopes by Optimization of ANFIS with GA, FFA and PSO by Jayanti Bharti, Pijush Samui

“…Some of the statistical errors such as Mean Square Error (MSE) values were 0.0148, 0.0182, 0.0159 in training and 0.1263, 0.0277 and 0.1289 in testing. …”
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On the Synergy of Optimizers and Activation Functions: A CNN Benchmarking Study by Khuraman Aziz Sayın, Necla Kırcalı Gürsoy, Türkay Yolcu, Arif Gürsoy

“…In this study, we present a comparative analysis of gradient descent-based optimizers frequently used in Convolutional Neural Networks (CNNs), including SGD, mSGD, RMSprop, Adadelta, Nadam, Adamax, Adam, and the recent EVE optimizer. …”
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Optimized Detection Algorithm for Vertical Irregularities in Vertical Curve Segments by Rong Xie, Chunjun Chen

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Research on formant estimation algorithm for high order optimal LPC root value screening by Hua LONG, Shumeng SU

“…The root determination threshold, optimal LP root value distribution, peak distribution of formant in spectral envelope and formant estimation error of speech digital resonance model constraints under different orders are investigated. …”
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Enhancing Drought Forecast Accuracy Through Informer Model Optimization by Jieru Wei, Wensheng Tang, Pakorn Ditthakit, Jiandong Shang, Hengliang Guo, Bei Zhao, Gang Wu, Yang Guo

“…The performance of these models was evaluated using the root mean square error (RMSE), Nash–Sutcliffe efficiency coefficient (NSE), and Mean Absolute Error (MAE). …”
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Optimizing document management and retrieval with multimodal transformers and knowledge graphs. by Yali Chen, Bin Hu, Yajuan Liu

“…Ablation experiments also confirm the indispensability of each module. Visual analysis further demonstrates the model's clear advantages in retrieval accuracy and efficiency, though error analysis reveals its shortcomings in handling long-tail entities and cross-modal ambiguity. …”
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Industrial data-driven machine learning soft sensing for optimal operation of etching tools by Feiyang Ou, Henrik Wang, Chao Zhang, Matthew Tom, Sthitie Bom, James F. Davis, Panagiotis D. Christofides

“…For PASS/FAIL classification, a data aggregation method is developed to enhance model predictive performance with larger training datasets. A statistical analysis method involving point-biserial correlation and the Mean Absolute Error (MAE) difference score is introduced to select the optimal candidate datasets for aggregation, further improving the effectiveness of data aggregation. …”
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Optimization Scheme for Modulation of Data Transmission Module in Endoscopic Capsule by Meiyuan Miao, Chen Ye, Zhiping Xu, Laiding Zhao, Jiafeng Yao

“…The scheme is analyzed in terms of the in-body channel. The analysis and discussion for the scheme in wireless body area networks (WBANs) are divided into three aspects: bit error rate (BER) performance, energy efficiency (EE), and spectrum efficiency (SE), and complexity. …”
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Structure Design and Optimization of Self-locking Under-actuated Gripper by Shuting He, Yi Shen, Xianling Dai, Beibei Qiu, Xianfeng Pan, Mingxin Yuan

“…Numerical test results show that， compared with the empirical method and the Fmincon algorithm， the target value error optimized by the genetic algorithm is reduced by 70% and 62.5%， and the maximum deviation of the gripper's clamping force is reduced by 78.3% and 61.4% respectively， which verifies the superiority of the genetic optimization design of the proposed under-actuated gripper， and satisfies the stable clamping requirement of the clamper through the balance of the knuckle forces.…”
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Investment feasibility and optimization strategies of RFID technology in logistics field by Jianghan Han, Haotian Ai, Ruifeng Li, Xudong Deng, Yiyang Wu, Jian Wang, Zhijun Wei

“…However, existing research mostly focuses on the theoretical application of technology, lacking support for investment feasibility analysis and system optimization strategies based on practical scenarios. …”
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Design optimization of pangolin inspired composites for enhanced energy absorption by Iman Karami Fath, Abbas Niknejad, Hadi Zare-Zardini

“…The Taguchi method set the optimal values for the parameter levels for the prediction of TAE of 11.2431 J and SAE of 2.3677 J/g, while the actual experimental result brought the percentage of error to 5.76% for TAE and 3.94% for SAE. …”
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Research on the Multi-Objective Optimal Design of Adjusting Mechanisms Considering Force Transmission Performance by Qi Yang, Mingxin Shan, Yangli Tian, Boyang Guan, Jingyu Zhai, Wei Sun

“…Through case studies, significant reductions in motion precision errors and the peak stagnation force and maximum differences in stagnation force were achieved, validating the feasibility of this optimization design approach.…”
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Optimized Predictive Coverage by Averaging Time‐Windowed Bayesian Distributions by Han‐Fang Hsueh, Anneli Guthke, Thomas Wöhling, Wolfgang Nowak

“…With the proposed routine, we explicitly capture the time‐varying impact of model error on prediction uncertainty. The length of the calibration window is optimized to maximize goal‐oriented statistical skill scores for predictive coverage. …”
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Optimization of fluoride removal by induced crystallization based on RSM methodology by ZHENG Weicheng, QIN Shulin, WANG Zhongquan, CHEN Xia

“…In order to investigate the fluoride removal effect of calcium fluorophosphate induced crystallization, Box-Behnken design (BBD) was used for calcium fluorophosphate induced crystallization fluoride removal experiments to develop a quadratic regression model with the fluoride ion removal rate as the response value, and to compare the significance of the effects of three parameters〔n(Ca)/n(F), n(P)/n(F), crystalline seed dosage〕 on the fluoride ion removal rate by analysis of variance (ANOVA). The process parameters of calcium fluorophosphate induced crystallization for fluoride removal were optimized by RSM, and the model was validated by the experimental results under the optimal process condition. …”
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On the Design of Near-Optimal Generalized Block-Based Spatial Modulation With Low Detection Complexity by Yen-Ming Chen, Wei-Lun Lin, Heng Lee, Tsung-Lin Chen

“…Secondly, a codebook-assisted tree-search detector (CATSD) is introduced, offering a 98% reduction in complexity compared to ML detection while maintaining near-ML error performance. Finally, an alternative codebook search method is presented, accompanied by a complexity analysis that reveals a favorable trade-off between performance and computational cost.…”
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Passive Drag Reduction Optimization for Complex Commercial Vehicle Models by G. Liao, M. Xue, L. Yue, H. Yang, P. Guo, X. Hu, Z. Wang, T. Ma

“…The local details of the optimization results are optimized, and the low-wind-resistance shapes of the cabs of the three styling styles are obtained. …”
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Kinetics of Sludge Superheated Steam Drying and Optimization of Process Parameters by Xukun Zhang, Pu Xing, Shengping Liu, Chengzhen Zhang, Weiliang Fu

“…According to response surface test analysis, the optimal drying process with relative unit energy consumption is steam temperature of 215°C, sludge mass of 25 g (corresponding sludge thickness of 8 mm), and steam flow of 30 m3/h. …”
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