Results 81 to 90 of about 17,247 (264)

Soft Computing Optimizer For Intelligent Control Systems Design: The Structure And Applications [PDF]

Journal of Systemics, Cybernetics and Informatics, 2003
Soft Computing Optimizer (SCO) as a new software tool for design of robust intelligent control systems is described. It is based on the hybrid methodology of soft computing and stochastic simulation.
Sergey A. Panfilov, Ludmila V. Litvintseva, Ilya S. Ulyanov, Kazuki Takahashi, Serguei V. Ulyanov, Alexander V. Yazenin, Takahide Hagiwara   +6 more
doaj  

Foundation Model‐Enabled Pathology‐Informed MRI Model for Preoperative Prediction of Vessels Encapsulating Tumor Clusters in Resectable Hepatocellular Carcinoma: A Multicenter Retrospective Study

Advanced Science, EarlyView.
PIVOT uses pathology‐derived morphologic and vascular representations from postoperative H&E and CD34 whole‐slide images to guide model development, while clinical inference requires only preoperative multiparametric MRI. Across five centers, PIVOT enabled accurate preoperative assessment of vessels encapsulating tumor clusters, stratified patients by ...
Zhehan Shen, Wanmin Liu, Xiaoming Li, Wenjie Zou, Yiman Li, Jie Yuan, Yasen Yimit, Shihang Wang, Linhao Qu, Hui Dong, Wei Chen, Ningyang Jia, Peijun Wang   +12 more
wiley   +1 more source

Detection and Elimination of a Potential Fire in Engine and Battery Compartments of Hybrid Electric Vehicles

Advances in Fuzzy Systems, 2012
This paper presents a novel fuzzy deterministic noncontroller type (FDNCT) system and an FDNCT inference algorithm (FIA). The FDNCT uses fuzzy inputs and produces a deterministic non-fuzzy output.
Macam S. Dattathreya, Harpreet Singh, Thomas Meitzler   +2 more
doaj   +1 more source

Fuzzy Inference Systems Optimization

CoRR, 2011
This paper compares various optimization methods for fuzzy inference system optimization. The optimization methods compared are genetic algorithm, particle swarm optimization and simulated annealing. When these techniques were implemented it was observed that the performance of each technique within the fuzzy inference system classification was context
Pretesh B. Patel, Tshilidzi Marwala
openaire   +2 more sources

Enhancing Specific Stiffness of Nano‐Architected Materials Through Generative AI and Active Learning

Advanced Science, EarlyView.
A structure‐centric generative framework searches voxelated design space directly, coupling a variational autoencoder with multi‐objective optimization and active learning to progressively expand the validated design domain. The discovered nano‐architectures, realized as pyrolytic carbon by two‐photon lithography, deliver 18–23% higher stiffness and 26–
Jinwook Yeo, Peter Serles, Donggeun Park, Julia R. Greer, Seunghwa Ryu   +4 more
wiley   +1 more source

Hardware‐Native Gaussian Sampling With Probabilistic Ising Machines for Modern Communication Paradigms

Advanced Science, EarlyView.
Probabilistic Ising machines are introduced as hardware‐native Gaussian samplers for edge communication workloads. Tunable variance and sampling density enable accurate distributions for Falcon‐class post‐quantum signatures and diffusion‐based semantic communication.
Davi Rodrigues, Andrea Grimaldi, Deborah Volpe, Youwei Bao, Shuhan Yang, Eleonora Grassucci, Giulio Siracusano, Massimo Chiappini, Mario Carpentieri, Hyunsoo Yang, Giovanni Finocchio   +10 more
wiley   +1 more source

Fuzzy Inference System Modeling for Corrosion Risk Management of Natural Gas Pipelines

Fuzzy Optimization and Modeling
Due to the complexity of operating conditions, predicting corrosion in natural gas pipelines is a challenge, and therefore its use in the gas industry is problematic. So, the present study employs corrosion risk management in control systems and decision
Nazila Adabavazeh, Mehrdad Nikbakht, Atefeh Amindoust, Sayed Ali Hassanzadeh-Tabrizi   +3 more
doaj   +1 more source

Physics‐Guided Multi‐Channel Restoration for Efficient and Accurate Atomic Force Microscopy Imaging

Advanced Science, EarlyView.
Schematic figure of restoring noisy atomic force micrscopy (AFM) image via physics‐guided multi‐channel restoration. The lighter neural network models with multiple‐channel input from auxiliary signals outperforms heavier model with single‐channel input.
Jaeuk Sung, Hongseok Kim, Seungjae Heo, Jin Tae Moon, Jangwoo Ko, Panithan Sriboriboon, Dong‐Gyu Lee, Sanghyun Jo, Hee Han, Jungho Ryu, Woo Lee, Jinseong Heo, Hyun‐Cheol Song, Yunseok Kim   +13 more
wiley   +1 more source

Mitochondrial Quality Control in Degenerative Musculoskeletal Diseases: Signaling Networks and Therapeutic Landscapes

Advanced Science, EarlyView.
Mitochondrial quality control (MQC) collapse redefines osteoarthritis, intervertebral disc degeneration, and osteoporosis as disorders of organelle dysfunction. Damaged mitochondria leak mtDNA and metabolites, driving cGAS‐STING inflammation, epigenetic reprogramming, and metabolic memory.
Haiyang Gao, Zhangrong Cheng, Xianglong Chen, Wenbo Wu, Wang Wu, Zimu Yu, Cao Yang, Yukun Zhang   +7 more
wiley   +1 more source

Data‐Driven and Physics‐Informed Modeling Perspectives for Soft Manipulators: From SINDy to Hybrid Intelligence

Advanced Science, EarlyView.
This Perspective charts the modeling landscape for soft manipulators, spanning sparse system identification, neural dynamics, physics‐informed models and hybrid intelligence. We examine how physics, data, sensing, adaptation and control can assume complementary roles within this landscape, and provide a framework for selecting modeling approaches ...
Wenbo Hui, Yunyi Wang, Teng Zhang, Yang Chen, Min Pan   +4 more
wiley   +1 more source