Systems and Soft Computing最新文献

英文中文

Neural networks optimization via Gauss–Newton based QR factorization on SARS-CoV-2 variant classification

Systems and Soft Computing

Pub Date : 2025-02-14 DOI: 10.1016/j.sasc.2025.200195

Mohammad Jamhuri , Mohammad Isa Irawan , Imam Mukhlash , Mohammad Iqbal , Ni Nyoman Tri Puspaningsih

Studies on the COVID-19 pandemic continue due to the potential mutation creating new variants. One response to be aware of the situation is by classifying SARS-CoV-2 variants. Neural networks (NNs)-based classifiers showed good accuracies but are known very costly in the learning process. Second-order optimization approaches are alternatives for NNs to work faster instead of the first-order ones. Still, it needs a huge memory usage. Therefore, we propose a new second-order optimization method for NNs, called QR-GN, to efficiently classify SARS-CoV-2 variants. The proposed method is derived from NNs and Gauss–Newton with QR factorization. The goal of this study is to classify SARS-CoV-2 variants given their spike protein sequences efficiently with high accuracy. In this study, the proposed method was demonstrated on a public dataset for the protein SARS-CoV-2. In the demonstrations, the proposed method outperformed other optimization methods in terms of memory usage and run time. Moreover, the proposed method can significantly elevate the accuracy classification for various NNs, such as: single layer perceptron, multilayer perceptron, and convolutional neural networks.

{"title":"Neural networks optimization via Gauss–Newton based QR factorization on SARS-CoV-2 variant classification","authors":"Mohammad Jamhuri , Mohammad Isa Irawan , Imam Mukhlash , Mohammad Iqbal , Ni Nyoman Tri Puspaningsih","doi":"10.1016/j.sasc.2025.200195","DOIUrl":"10.1016/j.sasc.2025.200195","url":null,"abstract":"<div><div>Studies on the COVID-19 pandemic continue due to the potential mutation creating new variants. One response to be aware of the situation is by classifying SARS-CoV-2 variants. Neural networks (NNs)-based classifiers showed good accuracies but are known very costly in the learning process. Second-order optimization approaches are alternatives for NNs to work faster instead of the first-order ones. Still, it needs a huge memory usage. Therefore, we propose a new second-order optimization method for NNs, called <em>QR-GN</em>, to efficiently classify SARS-CoV-2 variants. The proposed method is derived from NNs and Gauss–Newton with QR factorization. The goal of this study is to classify SARS-CoV-2 variants given their spike protein sequences efficiently with high accuracy. In this study, the proposed method was demonstrated on a public dataset for the protein SARS-CoV-2. In the demonstrations, the proposed method outperformed other optimization methods in terms of memory usage and run time. Moreover, the proposed method can significantly elevate the accuracy classification for various NNs, such as: single layer perceptron, multilayer perceptron, and convolutional neural networks.</div></div>","PeriodicalId":101205,"journal":{"name":"Systems and Soft Computing","volume":"7 ","pages":"Article 200195"},"PeriodicalIF":0.0,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143463876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Controllability results for multi-order impulsive neutral fuzzy functional integro-differential equations with finite delay

Systems and Soft Computing

Pub Date : 2025-02-10 DOI: 10.1016/j.sasc.2025.200202

T. Gunasekar , J. Thiravidarani , P. Raghavendran , B.N. Hanumagowda , Jagadish V. Tawade , Farrukh Yuldashev , Manish Gupta , M. Ijaz Khan

This manuscript focuses on examining the controllability of fuzzy mild solutions for nonlocal impulsive neutral functional integro-differential equations of the first and second order, including systems with finite delay. Furthermore, it explores the characteristics of fuzzy set-valued mappings over real variables, emphasizing important features such upper semi-continuity, convexity, normalcy, and compact support. The key conclusions are obtained by applying the Banach fixed-point theorem. The study makes extensive use of fundamental ideas from functional analysis, fuzzy set theory, and the Hausdorff metric. To demonstrate the practical application of the proposed method, a detailed example is provided.

引用次数: 0

Real-time data-driven estimation of production for point bottom sealing and cutting machines using machine learning

Systems and Soft Computing

Pub Date : 2025-02-08 DOI: 10.1016/j.sasc.2025.200194

Subha R , Diana F.R.I. M , Selvadass M

Demand for sophisticated, data-driven techniques to improve production efficiency has increased due to the expansion of the packaging sector, especially in the packaging of polypropylene (PP) flexible materials. PP-based materials offer a variety of packaging applications due to their robust and versatile qualities, but they also require careful production planning to maximize time and resources. By examining important factors that affect output rates and manufacturing costs, such as material dimensions, thickness, and machine cutting speed, this study investigates how predictive modeling may transform production forecasting. This study attempts to build reliable models with optimized hyperpameters to forecast production yield by integrating simple Machine Learning (ML) approaches, such as Support Vector Regression (SVR), Artificial Neural Networks (ANN), Gaussian Process Regression (GPR), and ensemble based approaches such as Random Forest Regression (RFR), Gradient Boosting Regression (GBR), AdaBoost Regression (ABR), Bagging Regression (BR) and Extra Trees Regression (ETR). A performance based comparison of these models, revealed that the ensemble based models using GBR and BR outperformed the others. Further, the prediction performance was improvised by incorporating them as base models and training a voting regressor model. The usefulness of the prediction model has been further demonstrated in creation of reference charts for effective estimation of cost and runtime.

{"title":"Real-time data-driven estimation of production for point bottom sealing and cutting machines using machine learning","authors":"Subha R , Diana F.R.I. M , Selvadass M","doi":"10.1016/j.sasc.2025.200194","DOIUrl":"10.1016/j.sasc.2025.200194","url":null,"abstract":"<div><div>Demand for sophisticated, data-driven techniques to improve production efficiency has increased due to the expansion of the packaging sector, especially in the packaging of polypropylene (PP) flexible materials. PP-based materials offer a variety of packaging applications due to their robust and versatile qualities, but they also require careful production planning to maximize time and resources. By examining important factors that affect output rates and manufacturing costs, such as material dimensions, thickness, and machine cutting speed, this study investigates how predictive modeling may transform production forecasting. This study attempts to build reliable models with optimized hyperpameters to forecast production yield by integrating simple Machine Learning (ML) approaches, such as Support Vector Regression (SVR), Artificial Neural Networks (ANN), Gaussian Process Regression (GPR), and ensemble based approaches such as Random Forest Regression (RFR), Gradient Boosting Regression (GBR), AdaBoost Regression (ABR), Bagging Regression (BR) and Extra Trees Regression (ETR). A performance based comparison of these models, revealed that the ensemble based models using GBR and BR outperformed the others. Further, the prediction performance was improvised by incorporating them as base models and training a voting regressor model. The usefulness of the prediction model has been further demonstrated in creation of reference charts for effective estimation of cost and runtime.</div></div>","PeriodicalId":101205,"journal":{"name":"Systems and Soft Computing","volume":"7 ","pages":"Article 200194"},"PeriodicalIF":0.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143402858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Enhancement of Bilateral Closed-Loop Functions in Stability Standards for Networked Control Systems with Transmission Delay

Systems and Soft Computing

Pub Date : 2025-02-07 DOI: 10.1016/j.sasc.2025.200201

Shenping Xiao , Jiajun Peng , Honghai Lian , Jianglin Huang

This research looks into a new method for analyzing systems of sampled data that have time delay and stability. The system's enhanced stability condition is suggested by constructing a new Lyapunov-Krasovskii (L-K) function containing both continuous and loop functions with full consideration of the information of the transmission interval and the transmission time delay. This new L-K function better captures the dynamics of the system, leading to more reasonable and effective stability analysis results. The sample control system's stability conditions are written as linear matrix inequalities using the integral inequality method and Lyapunov stability theory. Finally, by building matlab simulation experiments, the proposed Theorem 1 and Theorem 2 allow the maximum sampling bound to be significantly improved in two different numerical examples, and the proposed results are more effective and superior when compared with the existing literature.

引用次数: 0

Nonlinear PID controllers improved based on the quad rotor aircraft

Systems and Soft Computing

Pub Date : 2025-02-07 DOI: 10.1016/j.sasc.2025.200197

Hongcheng Zhou

Although linear controllers designed for the quad rotor aircraft have the obvious advantage of design information and availability of tools for control design relating to robot applications. However, due to trend of escalating performance, increasing maneuverability, unpredictable changes in environment, stronger dynamic coupling and nonlinearities necessitate more sophisticated control systems. The nonlinear controllers are designed for tracking and stabilization of the quad rotor aircraft. Design geometric nonlinear control methods, integral backstepping control, and affine nonlinear controllers based on PID controllers for the quad rotor aircraft. The improved algorithm for quad rotor aircraft has been optimized in terms of overshoot and adjustment time. The overshoot has been reduced by an average of about 15 %, and the adjustment time is also relatively short. The pitch, roll, and yaw angles tend to stabilize around 2 seconds with minimal fluctuations.

引用次数: 0

Citrus diseases detection and classification based on efficientnet-B5

Systems and Soft Computing

Pub Date : 2025-02-07 DOI: 10.1016/j.sasc.2025.200199

Abdullahi Lawal Rukuna , F.U. Zambuk , A.Y. Gital , Umar Muhammad Bello

The detection and classification of citrus diseases are critical for ensuring the health and productivity of citrus fruits. This research focuses on enhancing the accuracy and effectiveness of citrus disease detection and classification using the EfficientNet-B5 model. The dataset, sourced from Kaggle, includes images of various citrus diseases: black spot, canker, huanglongbing (greening), and healthy instances. To address class imbalance and improve data diversity, synthetic minority oversampling technique (SMOTE) and augmentation fusion were employed, resulting in 970 images per class. The preprocessed data were partitioned into training, validation, and test sets. The efficientNet-B5 model was trained and validated, achieving a remarkable accuracy of 99.22 %. The study also includes a comprehensive comparison with existing systems based on accuracy and loss curves, confusion matrices, and classification reports. The proposed system demonstrated superior performance, outperforming other models in terms of both accuracy and robustness, highlighting its potential for practical applications in citrus disease management.

{"title":"Citrus diseases detection and classification based on efficientnet-B5","authors":"Abdullahi Lawal Rukuna , F.U. Zambuk , A.Y. Gital , Umar Muhammad Bello","doi":"10.1016/j.sasc.2025.200199","DOIUrl":"10.1016/j.sasc.2025.200199","url":null,"abstract":"<div><div>The detection and classification of citrus diseases are critical for ensuring the health and productivity of citrus fruits. This research focuses on enhancing the accuracy and effectiveness of citrus disease detection and classification using the EfficientNet-B5 model. The dataset, sourced from Kaggle, includes images of various citrus diseases: black spot, canker, huanglongbing (greening), and healthy instances. To address class imbalance and improve data diversity, synthetic minority oversampling technique (SMOTE) and augmentation fusion were employed, resulting in 970 images per class. The preprocessed data were partitioned into training, validation, and test sets. The efficientNet-B5 model was trained and validated, achieving a remarkable accuracy of 99.22 %. The study also includes a comprehensive comparison with existing systems based on accuracy and loss curves, confusion matrices, and classification reports. The proposed system demonstrated superior performance, outperforming other models in terms of both accuracy and robustness, highlighting its potential for practical applications in citrus disease management.</div></div>","PeriodicalId":101205,"journal":{"name":"Systems and Soft Computing","volume":"7 ","pages":"Article 200199"},"PeriodicalIF":0.0,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143419791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A systematic assessment of sentiment analysis models on iraqi dialect-based texts

Systems and Soft Computing

Pub Date : 2025-02-07 DOI: 10.1016/j.sasc.2025.200203

Hafedh Hameed Hussein, Amir Lakizadeh

Social media allows individuals, groups, and companies to openly express their opinions, creating a rich resource for trend assessments through sentiment analysis. Sentiment Analysis (SA) uses natural language processing (NLP) to interpret these opinions from text. However, Arabic sentiment analysis faces challenges due to dialect variations, limited resources, and hidden sentiment words. This study proposes hybrid models combining Convolutional Neural Networks with Long Short-Term Memory called as CNN-LSTM, CNN with Gated Recurrent Unit called as CNN-GRU. and AraBERT, a deep transformer model, to enhance Iraqi sentiment analysis. These models were evaluated against various machine learning and deep learning models. For feature extraction, we utilized Continuous Bag of Words (CBOW) for deep learning models and BERT for the AraBERT model, while TF-IDF was used for machine learning models. According to the experimental results, the AraBERT model has been able to achieve superior performance and significantly improve the accuracy of sentiment analysis in case of Iraqi dialect-based texts.

引用次数: 0

Application of improved particle swarm optimization algorithm combined with genetic algorithm in shear wall design

Systems and Soft Computing

Pub Date : 2025-02-07 DOI: 10.1016/j.sasc.2025.200198

Wei Gao

In order to achieve the rationality and economy of shear wall layout, an improved algorithm was designed in the architectural design program. The improved algorithm is based on the basic framework of genetic algorithm and particle swarm optimization algorithm, first adjusting the inertia weight, and then introducing elimination mechanism and mutation rate control. A shear wall design model was constructed using an improved algorithm, which was applied to determine the layout of shear walls in a 28 story high-rise building in a certain city. The example results show that when using the designed shear wall design program for scheme design, the success rate reaches 100 %, which is 38.47 % higher than the original particle swarm optimization algorithm. The obtained optimization scheme has interlayer displacement angles of 1/2096 and 1/1800 in the vertical and horizontal directions, respectively, while the torsional displacement ratio in both directions is 1.0908 and the torsional period ratio is 0.7125. After optimizing the algorithm, the length of the shear wall material was saved by 10.97 %, effectively reducing the use of materials. This not only reduces construction costs, but also brings higher space utilization efficiency. The building design scheme obtained from this study not only meets national standards, but also has lower computational time costs. This study demonstrates the potential application of this design algorithm in solving traditional architectural design problems. This not only provides new tools for the field of architectural design, but also stimulates more interdisciplinary cooperation, integrating computer science, artificial intelligence technology more closely with building engineering.

{"title":"Application of improved particle swarm optimization algorithm combined with genetic algorithm in shear wall design","authors":"Wei Gao","doi":"10.1016/j.sasc.2025.200198","DOIUrl":"10.1016/j.sasc.2025.200198","url":null,"abstract":"<div><div>In order to achieve the rationality and economy of shear wall layout, an improved algorithm was designed in the architectural design program. The improved algorithm is based on the basic framework of genetic algorithm and particle swarm optimization algorithm, first adjusting the inertia weight, and then introducing elimination mechanism and mutation rate control. A shear wall design model was constructed using an improved algorithm, which was applied to determine the layout of shear walls in a 28 story high-rise building in a certain city. The example results show that when using the designed shear wall design program for scheme design, the success rate reaches 100 %, which is 38.47 % higher than the original particle swarm optimization algorithm. The obtained optimization scheme has interlayer displacement angles of 1/2096 and 1/1800 in the vertical and horizontal directions, respectively, while the torsional displacement ratio in both directions is 1.0908 and the torsional period ratio is 0.7125. After optimizing the algorithm, the length of the shear wall material was saved by 10.97 %, effectively reducing the use of materials. This not only reduces construction costs, but also brings higher space utilization efficiency. The building design scheme obtained from this study not only meets national standards, but also has lower computational time costs. This study demonstrates the potential application of this design algorithm in solving traditional architectural design problems. This not only provides new tools for the field of architectural design, but also stimulates more interdisciplinary cooperation, integrating computer science, artificial intelligence technology more closely with building engineering.</div></div>","PeriodicalId":101205,"journal":{"name":"Systems and Soft Computing","volume":"7 ","pages":"Article 200198"},"PeriodicalIF":0.0,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evaluation of basic sports actions for students based on DTW posture matching algorithm

Systems and Soft Computing

Pub Date : 2025-02-07 DOI: 10.1016/j.sasc.2025.200196

Zhonghai Chen , Tengyu Zhang

In the evaluation of basic sports movements for students, traditional evaluation methods are usually limited by static indicators, making it difficult to comprehensively capture students' performance in dynamic sports movements. Therefore, the study proposes a student sports basic action evaluation method based on the dynamic time warping posture matching algorithm, focusing on the action recognition, and the method is verified. These experiments confirmed that the average error of this proposed method in positioning accuracy testing was significantly smaller than the other two comparison algorithms, with an average error of 11.43 mm, 15.35 mm, and 20.38 mm on the X, Y, and Z axes, respectively. Moreover, its recognition rate for broadcast gymnastics was as high as 99.5 %. To verify the practical application significance of the research, the score of student S8 reached 9.95. After 8 weeks of training, the average muscle mass was increased by 52.9 %, and the maximum oxygen uptake was increased by 34.1 %. In contrast, student S9 with a score of 5.56 showed a relatively small improvement, with a 25.8 % increase in muscle mass and only a 19.1 % increase in maximum oxygen uptake. The innovative application of the posture matching algorithm in the evaluation of basic sports movements of students provides a feasible and effective method for improving the level of physical education and sports health management.

{"title":"Evaluation of basic sports actions for students based on DTW posture matching algorithm","authors":"Zhonghai Chen , Tengyu Zhang","doi":"10.1016/j.sasc.2025.200196","DOIUrl":"10.1016/j.sasc.2025.200196","url":null,"abstract":"<div><div>In the evaluation of basic sports movements for students, traditional evaluation methods are usually limited by static indicators, making it difficult to comprehensively capture students' performance in dynamic sports movements. Therefore, the study proposes a student sports basic action evaluation method based on the dynamic time warping posture matching algorithm, focusing on the action recognition, and the method is verified. These experiments confirmed that the average error of this proposed method in positioning accuracy testing was significantly smaller than the other two comparison algorithms, with an average error of 11.43 mm, 15.35 mm, and 20.38 mm on the X, Y, and Z axes, respectively. Moreover, its recognition rate for broadcast gymnastics was as high as 99.5 %. To verify the practical application significance of the research, the score of student S8 reached 9.95. After 8 weeks of training, the average muscle mass was increased by 52.9 %, and the maximum oxygen uptake was increased by 34.1 %. In contrast, student S9 with a score of 5.56 showed a relatively small improvement, with a 25.8 % increase in muscle mass and only a 19.1 % increase in maximum oxygen uptake. The innovative application of the posture matching algorithm in the evaluation of basic sports movements of students provides a feasible and effective method for improving the level of physical education and sports health management.</div></div>","PeriodicalId":101205,"journal":{"name":"Systems and Soft Computing","volume":"7 ","pages":"Article 200196"},"PeriodicalIF":0.0,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143419792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Personalized icon design model based on improved Faster-RCNN 基于改进型 Faster-RCNN 的个性化图标设计模型

Systems and Soft Computing

Pub Date : 2025-01-30 DOI: 10.1016/j.sasc.2025.200193

Zhikun Wang , Jiaqian Wang

In the digital age, as an important element of visual communication, icons have an increasing demand for personalized design. In order to meet the personalized icon design needs of students, education, management, and design fields, a personalized icon design model based on a faster regional suggestion network is proposed. Firstly, the convolutional neural network is improved to extract the multi-attribute features of icons. The transfer learning is used to optimize model parameter sharing. Then, the improved faster region-Convolutional network model is adopted for object detection, enhancing the ability to classify and recognize icons. The designed method had a recognition accuracy of over 80% in different types of icons. Among different types of icon data, the recognition accuracy of office type icons was the worst, with a recognition accuracy of 81.3%. The recognition accuracy of traffic type icons was the highest, with a recognition accuracy of 98.3%. The model had a processing time of less than 350 ms for different types of icons, with the shortest processing time of 233 ms for social media icons. The research results indicate that the proposed model has high practicality in icon personalized design, and can provide convenient tool support for designers, students, teachers, and users in the field of education management, promoting the popularization and application of personalized icon design.

{"title":"Personalized icon design model based on improved Faster-RCNN","authors":"Zhikun Wang , Jiaqian Wang","doi":"10.1016/j.sasc.2025.200193","DOIUrl":"10.1016/j.sasc.2025.200193","url":null,"abstract":"<div><div>In the digital age, as an important element of visual communication, icons have an increasing demand for personalized design. In order to meet the personalized icon design needs of students, education, management, and design fields, a personalized icon design model based on a faster regional suggestion network is proposed. Firstly, the convolutional neural network is improved to extract the multi-attribute features of icons. The transfer learning is used to optimize model parameter sharing. Then, the improved faster region-Convolutional network model is adopted for object detection, enhancing the ability to classify and recognize icons. The designed method had a recognition accuracy of over 80% in different types of icons. Among different types of icon data, the recognition accuracy of office type icons was the worst, with a recognition accuracy of 81.3%. The recognition accuracy of traffic type icons was the highest, with a recognition accuracy of 98.3%. The model had a processing time of less than 350 ms for different types of icons, with the shortest processing time of 233 ms for social media icons. The research results indicate that the proposed model has high practicality in icon personalized design, and can provide convenient tool support for designers, students, teachers, and users in the field of education management, promoting the popularization and application of personalized icon design.</div></div>","PeriodicalId":101205,"journal":{"name":"Systems and Soft Computing","volume":"7 ","pages":"Article 200193"},"PeriodicalIF":0.0,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143471486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

下一页尾页

类型

全部化学•材料生命科学医学物理工程技术环境•农林材料科学地球科学法学管理学化学环境科学与生态学计算机科学教育学经济学农林科学人文科学生物学数学物理与天体物理心理学综合性期刊其他工业工程理学历史学农学文学信息工程

数据库

全部 ACS Publications Elsevier ieeexplore Springer The Royal Society of Chemistry Wiley

期刊

Systems and Soft Computing

全部 Acc. Chem. Res. ACS Applied Bio Materials ACS Appl. Electron. Mater. ACS Appl. Energy Mater. ACS Appl. Mater. Interfaces ACS Appl. Nano Mater. ACS Appl. Polym. Mater. ACS BIOMATER-SCI ENG ACS Catal. ACS Cent. Sci. ACS Chem. Biol. ACS Chemical Health & Safety ACS Chem. Neurosci. ACS Comb. Sci. ACS Earth Space Chem. ACS Energy Lett. ACS Infect. Dis. ACS Macro Lett. ACS Mater. Lett. ACS Med. Chem. Lett. ACS Nano ACS Omega ACS Photonics ACS Sens. ACS Sustainable Chem. Eng. ACS Synth. Biol. Anal. Chem. BIOCHEMISTRY-US Bioconjugate Chem. BIOMACROMOLECULES Chem. Res. Toxicol. Chem. Rev. Chem. Mater. CRYST GROWTH DES ENERG FUEL Environ. Sci. Technol. Environ. Sci. Technol. Lett. Eur. J. Inorg. Chem. IND ENG CHEM RES Inorg. Chem. J. Agric. Food. Chem. J. Chem. Eng. Data J. Chem. Educ. J. Chem. Inf. Model. J. Chem. Theory Comput. J. Med. Chem. J. Nat. Prod. J PROTEOME RES J. Am. Chem. Soc. LANGMUIR MACROMOLECULES Mol. Pharmaceutics Nano Lett. Org. Lett. ORG PROCESS RES DEV ORGANOMETALLICS J. Org. Chem. J. Phys. Chem. J. Phys. Chem. A J. Phys. Chem. B J. Phys. Chem. C J. Phys. Chem. Lett. Analyst Anal. Methods Biomater. Sci. Catal. Sci. Technol. Chem. Commun. Chem. Soc. Rev. CHEM EDUC RES PRACT CRYSTENGCOMM Dalton Trans. Energy Environ. Sci. ENVIRON SCI-NANO ENVIRON SCI-PROC IMP ENVIRON SCI-WAT RES Faraday Discuss. Food Funct. Green Chem. Inorg. Chem. Front. Integr. Biol. J. Anal. At. Spectrom. J. Mater. Chem. A J. Mater. Chem. B J. Mater. Chem. C Lab Chip Mater. Chem. Front. Mater. Horiz. MEDCHEMCOMM Metallomics Mol. Biosyst. Mol. Syst. Des. Eng. Nanoscale Nanoscale Horiz. Nat. Prod. Rep. New J. Chem. Org. Biomol. Chem. Org. Chem. Front. PHOTOCH PHOTOBIO SCI PCCP Polym. Chem.

﹀