標(biāo)題: Titlebook: Intelligent Systems; Proceedings of 3rd I Siba K. Udgata,Srinivas Sethi,Xiao-Zhi Gao Conference proceedings 2024 The Editor(s) (if applicab [打印本頁(yè)] 作者: 喝水 時(shí)間: 2025-3-21 16:04
書目名稱Intelligent Systems影響因子(影響力)
書目名稱Intelligent Systems影響因子(影響力)學(xué)科排名
書目名稱Intelligent Systems網(wǎng)絡(luò)公開度
書目名稱Intelligent Systems網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Intelligent Systems被引頻次
書目名稱Intelligent Systems被引頻次學(xué)科排名
書目名稱Intelligent Systems年度引用
書目名稱Intelligent Systems年度引用學(xué)科排名
書目名稱Intelligent Systems讀者反饋
書目名稱Intelligent Systems讀者反饋學(xué)科排名
作者: Counteract 時(shí)間: 2025-3-21 22:37 作者: 美食家 時(shí)間: 2025-3-22 02:51 作者: 奇怪 時(shí)間: 2025-3-22 07:13
J. Premalatha,S. Aswin,D. JaiHari,K. Karamchand Subash extensive examples and exercises without the need for a com.Differential Equations for Scientists and Engineers. is a book designed with students in mind. It attempts to take a concise, simple, and no-frills approach to differential equations. The?approach used in this?text is to give students exte作者: 刺激 時(shí)間: 2025-3-22 11:18
S. Anandamurugan,P. Jayaprakash,S. Mounika,R. Narendranath extensive examples and exercises without the need for a com.Differential Equations for Scientists and Engineers. is a book designed with students in mind. It attempts to take a concise, simple, and no-frills approach to differential equations. The?approach used in this?text is to give students exte作者: 窩轉(zhuǎn)脊椎動(dòng)物 時(shí)間: 2025-3-22 15:33
Lalitha Krishnasamy,M. Aparnaa,G. Deepa Prabha,T. Kavya extensive examples and exercises without the need for a com.Differential Equations for Scientists and Engineers. is a book designed with students in mind. It attempts to take a concise, simple, and no-frills approach to differential equations. The?approach used in this?text is to give students exte作者: Bumble 時(shí)間: 2025-3-22 19:24
Effect of the Longitudinal Strain of PM Fiber on the Signal Group Velocity,ed this way is the longitudinal tension of the fiber. A set of measurements leading to approval of the suitability of polarization for this purpose was performed. This paper analyzes the dependency of differential group delay of the signal in slow and fast axes of the birefringent optical fiber on t作者: 不能逃避 時(shí)間: 2025-3-23 00:28
Machine Learning Algorithms Aided Disease Diagnosis and Prediction of Grape Leaf, a number of diseases, including black rot esca black measles, blight isariopsis, and others, in order to predict disease occurrence. For the prediction of leaf diseases, convolution neural networks combined with data augmentation have increased the degree of verification. For illness predictive ana作者: calumniate 時(shí)間: 2025-3-23 03:03
Optimized Fuzzy PI Regulator for Frequency Regulation of Distributed Power System,gion nonwarm framework is utilized. The advantage of the stated fuzzy PI regulator is shown with the help of contrasting the outputs. All real structure shows non-straight nature, subsequently, traditional regulators are not generally ready to give great and precise outcomes. So fuzzy-logic controll作者: 定點(diǎn) 時(shí)間: 2025-3-23 07:42
Detecting Depression Using Quality-of-Life Attributes with Machine Learning Techniques,iscover that they must treat mental health problems like depression despite having little or no formal training in how to do so. There is proof that an integrated strategy, where doctors regularly screen patients for mental health issues and collaborate with psychologists and other mental health spe作者: promote 時(shí)間: 2025-3-23 13:12
Patient Satisfaction Through Interpretable Machine Learning Approach,ecisions. An individual’s specific health requirements, individualised treatment, and desired health results are of the utmost importance in the period of patient-centered care. Across the past decade, treatment delivery, management, and reimbursement practices?have all been impacted by patient sati作者: 細(xì)查 時(shí)間: 2025-3-23 15:12
Predicting the Thyroid Disease Using Machine Learning Techniques,may be produced insufficiently or excessively as a result of its potential malfunction. There are various thyroid types including Hyperthyroidism, Hypothyroidism, Thyroid Cancer Thyroiditis, swelling of the thyroid. A goiter is an enlarged thyroid gland. When your thyroid gland produces more thyroid作者: Negligible 時(shí)間: 2025-3-23 20:10
An Automatic Traffic Sign Recognition and Classification Model Using Neural Networks, researchers. To accomplish their assessment, specialists employed Artificial Intelligence, deep learning, and image processing tools. Convolutional Neural Networks (CNN) are deep learning-based designs that have sparked a new and ongoing research into traffic symbol classifications and recognition 作者: 變色龍 時(shí)間: 2025-3-24 01:03 作者: MUMP 時(shí)間: 2025-3-24 05:56 作者: AMEND 時(shí)間: 2025-3-24 07:22
Japanese Encephalitis Symptom Prediction Using Machine Learning Algorithm, occurring of JEV. Research says that Japanese Encephalitis is a flavivirus related to West Nile Virus, Yellow Fever and Dengue and it is escalated by mosquitoes. Japanese Encephalitis is although rare, but the fatality rate is around 30%. Till now there is no cure for JEV, the entire treatment is f作者: NAUT 時(shí)間: 2025-3-24 13:26
Smart Skin-Proto: A Mobile Skin Disorders Recognizer Model,stems that mainly includes the use of mobile health technology which is quite efficient. Moreover, this field is slightly shifting and also indicating interest towards the smart and intelligent models as there are quite a lot of benefits associated with it like cost decrement, easy to understand and作者: Resection 時(shí)間: 2025-3-24 17:38 作者: Factorable 時(shí)間: 2025-3-24 22:26 作者: 優(yōu)雅 時(shí)間: 2025-3-24 23:21 作者: Exclude 時(shí)間: 2025-3-25 03:55
Supervised Learning Approaches on the Prediction of Diabetic Disease in Healthcare,nt organs in the human body. Diabetes can cause a variety of slow bad?consequences if not?detected and left without given medical care. The emergence of machine learning approaches, on the other hand, solves this crucial issue. The purpose and objectives of this work is to build a prototypical model作者: 致敬 時(shí)間: 2025-3-25 11:19
Solar Powered Smart Home Automation and Smart Health Monitoring with IoT,e automation system. The sensors are spread all across the entrance Gate, corridor, room and kitchen. This (IOT) design prototype has LCD transistor which keep on provides the information. We have also use Wi-Fi technology for online control and monitoring. we also have an LCD which keeps us providi作者: absolve 時(shí)間: 2025-3-25 14:13
Seasonal-Wise Occupational Accident Analysis Using Deep Learning Paradigms,d for automating the safety precautions for employees in the industrial sectors such as mining, metals, construction, chemical, and electrical sections. However, the automation cannot be accurate as the data analysis is based on real-life data. Since the real-life data are imbalanced and uncertain, 作者: Classify 時(shí)間: 2025-3-25 17:58 作者: 凌辱 時(shí)間: 2025-3-25 21:08 作者: bronchiole 時(shí)間: 2025-3-26 03:44 作者: 發(fā)起 時(shí)間: 2025-3-26 07:19
2367-3370 a reference resource for researchers and practitioners in a.This book features best selected research papers presented at the Third International Conference on Machine Learning, Internet of Things and Big Data (ICMIB 2023) held at Indira Gandhi Institute of Technology, Sarang, India, during March 1作者: 賞錢 時(shí)間: 2025-3-26 11:12
MLFP: Machine Learning Approaches for Flood Prediction in Odisha State,rning models. Before this process, the data is cleaned and pre-processed, and the dataset for training is split into a train set and a test set in an 80:20 ratio. Then the accuracy of each model is compared and the confusion matrix parameters are taken to evaluate and analyze. In the end, the best model is chosen by comparing the accuracy.作者: 休息 時(shí)間: 2025-3-26 12:46
Machine Learning Algorithms Aided Disease Diagnosis and Prediction of Grape Leaf,lytics, a proper confusion matrix for support vector machines driven by CNN was created. Along with k-mean clustering, fuzzy logic with accurate feature extraction, and color moment definition, we also compared our results with these techniques. The findings indicate a higher effectiveness of up to 95% in correctly predicting grapes leaf disease.作者: 除草劑 時(shí)間: 2025-3-26 17:37
Conference proceedings 2024in smart environments, smart health, smart city, wireless networks, big data, cloud computing, business intelligence, Internet security, pattern recognition, predictive analytics applications in health care, sensor networks and social sensing, and statistical analysis of search techniques..作者: 有斑點(diǎn) 時(shí)間: 2025-3-26 23:55
Optimized Fuzzy PI Regulator for Frequency Regulation of Distributed Power System,ed PI selector and Bacteria Foraging optimization algorithm (BFOA) adjusted PI selector is demonstrated. It is seen that the Fuzzy PI regulator is more effective for controlling frequency relative to the PI regulator.作者: 使習(xí)慣于 時(shí)間: 2025-3-27 02:53 作者: Solace 時(shí)間: 2025-3-27 08:07 作者: DOSE 時(shí)間: 2025-3-27 10:23
A Fuzzy Logic Based Trust Evaluation Model for IoT,ed on the resultant trust value, the IoT nodes are classified into three categories: Not Trustworthy, Not Sure and Trustworthy. An IoT node which belongs to Trustworthy only gets the access to forward the data packets or communicate with other IoT nodes. The Not Trustworthy and Not Sure IoT nodes are set to sleep mode for power conservation.作者: 羊齒 時(shí)間: 2025-3-27 14:44
Supervised Learning Approaches on the Prediction of Diabetic Disease in Healthcare,sed in the experiments. The Precision, Accuracy, Recall, F-Measure, and ROC Area are all used to calculate the efficiency of the above three algorithms. The correctness and accuracy of a classification system is measured by the number of occurrences that are correctly classified and those that are mistakenly classified.作者: 創(chuàng)造性 時(shí)間: 2025-3-27 20:36
Vision-Based Cyclist Travel Lane and Helmet Detection, classifier provided the highest training accuracy of 99.53% and testing accuracy of 87.83% for cyclists’ helmet detection. In future, this system can also serve as a small part of autonomous driver assistance systems by detecting the right lane.作者: 壕溝 時(shí)間: 2025-3-28 01:23 作者: 單調(diào)性 時(shí)間: 2025-3-28 05:31 作者: BRAND 時(shí)間: 2025-3-28 08:13 作者: judiciousness 時(shí)間: 2025-3-28 11:37 作者: tenosynovitis 時(shí)間: 2025-3-28 17:18 作者: ELUC 時(shí)間: 2025-3-28 19:18
An Automatic Traffic Sign Recognition and Classification Model Using Neural Networks, to verify the proposed model for an implanted application because of its softness and reduced number of boundaries (0.38 million) based on the improved LeNet-5 structure. The outcomes are advantageous, demonstrating the effectiveness of the discussed strategy.作者: florid 時(shí)間: 2025-3-28 23:04 作者: RLS898 時(shí)間: 2025-3-29 04:43
SoundMind: A Machine Learning and Web-Based Application for Depression Detection and Cure,ied out based on the classification result implemented using Logistic Regression. The model predicts the results with 91.85% test accuracy, 93% precision, 99% recall, and 96% f1 score. The above-mentioned models are deployed on the web application. The web application not only helps in predicting me作者: 現(xiàn)實(shí) 時(shí)間: 2025-3-29 09:23
Japanese Encephalitis Symptom Prediction Using Machine Learning Algorithm,m, Tamil Nadu, Bihar, Goa and Manipur. The impacting factors include Climate, Rice Distribution, Livestock Distribution, Population Density, Specific Age Group Density, Urban/Rural Category and Elevation. Impacting Factors may change with the location. Here we have used Machine learning algorithms l作者: sundowning 時(shí)間: 2025-3-29 13:31
Smart Skin-Proto: A Mobile Skin Disorders Recognizer Model, called ‘Smart Skin-Proto’ is developed. Then its usage in skin cancer assessment is also highlighted and upon implementation, the model records optimal performance which records an accuracy of 96.2% with 15 decision trees count. Also the overall latency of this application is less than other existi作者: IOTA 時(shí)間: 2025-3-29 18:26 作者: 代替 時(shí)間: 2025-3-29 20:43
Solar Powered Smart Home Automation and Smart Health Monitoring with IoT,cted condition which may occur when the owner is not present in home and it also notify the owner about the problem that has occurred. All the power requirements of smart homes are met by a self-generated solar power.作者: 召集 時(shí)間: 2025-3-30 01:37 作者: Foreshadow 時(shí)間: 2025-3-30 07:38
2367-3370 ing, business intelligence, Internet security, pattern recognition, predictive analytics applications in health care, sensor networks and social sensing, and statistical analysis of search techniques..978-981-99-3931-2978-981-99-3932-9Series ISSN 2367-3370 Series E-ISSN 2367-3389 作者: 清楚 時(shí)間: 2025-3-30 10:34
J. Premalatha,S. Aswin,D. JaiHari,K. Karamchand Subash the subject will develop a fundamental framework with which to pursue more advanced material. ?This book is designed for undergraduate students with some basic knowledge of precalculus algebra and a first course in calculus..?.978-1-4614-7297-1Series ISSN 1867-5506 Series E-ISSN 1867-5514 作者: 顛簸地移動(dòng) 時(shí)間: 2025-3-30 14:37 作者: 費(fèi)解 時(shí)間: 2025-3-30 17:24
Lalitha Krishnasamy,M. Aparnaa,G. Deepa Prabha,T. Kavya the subject will develop a fundamental framework with which to pursue more advanced material. ?This book is designed for undergraduate students with some basic knowledge of precalculus algebra and a first course in calculus..?.978-1-4614-7297-1Series ISSN 1867-5506 Series E-ISSN 1867-5514 作者: scrutiny 時(shí)間: 2025-3-30 21:30
Rajalaxmi Padhy,Alisha Samal,Sanjit Kumar Dash,Jibitesh Mishra作者: 灰心喪氣 時(shí)間: 2025-3-31 01:18 作者: RENIN 時(shí)間: 2025-3-31 05:10
Sushruta Mishra,Shubham Suman,Aritra Nandi,Smaraki Bhaktisudha,Kshira Sagar Sahoo作者: Grasping 時(shí)間: 2025-3-31 09:17
S. Preethi,T. Meeradevi,K. Mohammed Kaif,S. Hema,M. Monikraj作者: 使入迷 時(shí)間: 2025-3-31 15:11
Riyam Patel,Borra Sivaiah,Punyaban Patel,Bibhudatta Sahoo作者: Mosaic 時(shí)間: 2025-3-31 17:50 作者: Choreography 時(shí)間: 2025-4-1 00:27
Subasish Mohapatra,Kunaram Tudu,Amlan Sahoo,Subhadarshini Mohanty,Chandan Marandi作者: Isometric 時(shí)間: 2025-4-1 04:18
