標(biāo)題: Titlebook: Algorithms in Machine Learning Paradigms; Jyotsna Kumar Mandal,Somnath Mukhopadhyay,Kousik D Book 2020 Springer Nature Singapore Pte Ltd. [打印本頁(yè)] 作者: 夾子 時(shí)間: 2025-3-21 19:23
書(shū)目名稱Algorithms in Machine Learning Paradigms影響因子(影響力)
書(shū)目名稱Algorithms in Machine Learning Paradigms影響因子(影響力)學(xué)科排名
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書(shū)目名稱Algorithms in Machine Learning Paradigms網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書(shū)目名稱Algorithms in Machine Learning Paradigms被引頻次
書(shū)目名稱Algorithms in Machine Learning Paradigms被引頻次學(xué)科排名
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書(shū)目名稱Algorithms in Machine Learning Paradigms讀者反饋
書(shū)目名稱Algorithms in Machine Learning Paradigms讀者反饋學(xué)科排名
作者: prostatitis 時(shí)間: 2025-3-22 00:01
https://doi.org/10.1007/978-3-642-91468-3indicative parameters for disease diagnosis. Finally, the major vessels are classified as artery and vein sets to differentiate from the newly generated and unwanted blood vessels. This network was trained with the training and testing images of DRIAVE/RITE database for segmentation and artery vein 作者: commonsense 時(shí)間: 2025-3-22 00:38
https://doi.org/10.1007/978-3-642-91468-3 the expensive hardware resources by companies and institutes. However, to satisfy the need for resources of the users on time, Cloud Service Provider (CSP) must have to maintain the Quality of Service (QoS). Service Level Agreement (SLA) is done between the Datacenters and its end users. Minimizati作者: STENT 時(shí)間: 2025-3-22 07:10
Der Einphasenwechselstrommotor,odes for the future time frame based on their past observation. For this purpose, we use the Elman recurrent neural network (ERNN)-based learning tool to determine the behavior of the mobile nodes of the network in the future time frame.作者: Myocarditis 時(shí)間: 2025-3-22 12:46
https://doi.org/10.1007/978-3-642-86125-3, these solutions also require an observed attractor to check the similarity with the experimental attractor. This research overcomes the aforementioned constraint and flaw of the past models. In this research, a Real Coded Genetic Algorithm(RCGA) based optimization technique for optimizing the init作者: VAN 時(shí)間: 2025-3-22 15:06 作者: Interstellar 時(shí)間: 2025-3-22 20:25 作者: BRAND 時(shí)間: 2025-3-23 00:15
A Linear Regression-Based Resource Utilization Prediction Policy for Live Migration in Cloud Comput the expensive hardware resources by companies and institutes. However, to satisfy the need for resources of the users on time, Cloud Service Provider (CSP) must have to maintain the Quality of Service (QoS). Service Level Agreement (SLA) is done between the Datacenters and its end users. Minimizati作者: 招募 時(shí)間: 2025-3-23 03:02
Stable Neighbor-Node Prediction with Multivariate Analysis in Mobile Ad Hoc Network Using RNN Modelodes for the future time frame based on their past observation. For this purpose, we use the Elman recurrent neural network (ERNN)-based learning tool to determine the behavior of the mobile nodes of the network in the future time frame.作者: 持久 時(shí)間: 2025-3-23 09:35 作者: 財(cái)主 時(shí)間: 2025-3-23 10:46 作者: Conflict 時(shí)間: 2025-3-23 16:16 作者: Chemotherapy 時(shí)間: 2025-3-23 20:17
1860-949X al rule-based learning, feature extraction-based learning, optimization-based learning, quantum-inspired learning, multi-criteria-based learning and hybrid intelligence-based learning...?.978-981-15-1043-4978-981-15-1041-0Series ISSN 1860-949X Series E-ISSN 1860-9503 作者: MARS 時(shí)間: 2025-3-23 23:10 作者: ineptitude 時(shí)間: 2025-3-24 04:01
https://doi.org/10.1007/978-3-662-39624-7odel is capable of extracting the seasonal pattern from the training set and forecasting the future pattern. This model makes use of Self-organizing map (SOM) for clustering similar patterns. Performance of the model is evaluated using Rainfall data and Milk Production data.作者: 波動(dòng) 時(shí)間: 2025-3-24 10:34 作者: 內(nèi)部 時(shí)間: 2025-3-24 11:17 作者: 萬(wàn)花筒 時(shí)間: 2025-3-24 15:53 作者: thyroid-hormone 時(shí)間: 2025-3-24 21:06
Recognizing Human Emotions from Facial Images by Landmark Triangulation: A Combined Circumcenter-Insuch features is utilized for the purpose of discrimination of one expression from another using MultiLayer Perceptron (MLP) classifier in images containing facial expressions available in various benchmark databases. Results obtained by applying this method found to be extremely encouraging.作者: 雪白 時(shí)間: 2025-3-24 23:16 作者: 按等級(jí) 時(shí)間: 2025-3-25 04:17 作者: abysmal 時(shí)間: 2025-3-25 10:56 作者: Introvert 時(shí)間: 2025-3-25 14:32
Tracking Changing Human Emotions from Facial Image Sequence by Landmark Triangulation: An Incircle-cation of different emotional transitions from various face image sequences. Results of the proposed method obtained by application on various benchmark image databases are found to be quite impressive and encouraging compared to existing state-of-the-art technique.作者: 率直 時(shí)間: 2025-3-25 18:15 作者: Gleason-score 時(shí)間: 2025-3-25 21:43
,?Weltliteratur‘ zuerst bei Wieland,e which in turn may cause financial losses as well as bring about a decline in the firm’s market performance. This paper deals with the development of a strictly fact-based expert system for appropriate supplier selection and shows how rules can be broken down into atomic clauses.作者: Verify 時(shí)間: 2025-3-26 00:17
Der einheitliche EU-Zahlungsverkehroncept of score function and accuracy function of H–ITFN are defined and H–ITF prioritized weighted averaging and geometric operators based on Einstein operations are developed. Some desirable properties of the proposed operators are investigated in detail. A method for ordering the alternatives in 作者: 執(zhí)拗 時(shí)間: 2025-3-26 07:44 作者: BUST 時(shí)間: 2025-3-26 11:01 作者: 小故事 時(shí)間: 2025-3-26 12:59
https://doi.org/10.1007/978-3-662-39624-7em of seasonality. A few hybrid fuzzy time series models investigated the problem of forecasting in the presence of seasonal variation. But these techniques follow complex computational procedures. The aim of this present study is to develop a new fuzzy time series forecasting model that can process作者: 租約 時(shí)間: 2025-3-26 19:46
https://doi.org/10.1007/978-3-662-39624-7ect of the agricultural industry. It is quite challenging to automatically classify fruits and vegetables from digital images. The task of automatic classification becomes more difficult when the image is captured from a different viewing angle. This paper proposes a complete texture-based approach 作者: 郊外 時(shí)間: 2025-3-26 23:51
https://doi.org/10.1007/978-3-642-91468-3iabetic Retinopathy (PDR) is the advanced stage out of four major progressive stages of DR, where high risk of visual impairments occur. This work shows a deep learning-based automated method for detection of early signs of Proliferative Diabetic Retinopathy at the optic disc area in human retina. H作者: 不遵守 時(shí)間: 2025-3-27 03:11 作者: Motilin 時(shí)間: 2025-3-27 05:40 作者: Highbrow 時(shí)間: 2025-3-27 11:12 作者: thwart 時(shí)間: 2025-3-27 15:09
Der Einphasenwechselstrommotor, receiver as well as transmitter point in the network. This network maintains the wireless connections with the neighbor nodes and establishes a connecting link between the source–destination (s-d) pair. The route in this type of network is highly unstable due to the mobility of the nodes. So, to co作者: insert 時(shí)間: 2025-3-27 19:36
https://doi.org/10.1007/978-3-642-86125-3ng the strange chaotic behavior and security of using it in different applications. Using a single initial seed or a set of seed values for an application is a threat to its security. The unique seed for each execution of an application will make the system more secure and robust. In last two decade作者: Hirsutism 時(shí)間: 2025-3-27 23:38
Book 2020ons, including prediction, concept learning, explanation-based learning, case-based (exemplar-based) learning, statistical rule-based learning, feature extraction-based learning, optimization-based learning, quantum-inspired learning, multi-criteria-based learning and hybrid intelligence-based learning...?.作者: 指數(shù) 時(shí)間: 2025-3-28 04:37 作者: Emasculate 時(shí)間: 2025-3-28 06:18 作者: patella 時(shí)間: 2025-3-28 11:41
Algorithms in Machine Learning Paradigms978-981-15-1041-0Series ISSN 1860-949X Series E-ISSN 1860-9503 作者: 正式演說(shuō) 時(shí)間: 2025-3-28 17:50
Jyotsna Kumar Mandal,Somnath Mukhopadhyay,Kousik DDiscusses machine learning applications.Includes a wide variety of problems using learning algorithms along with applications.Comprises chapters from experts in the field作者: 許可 時(shí)間: 2025-3-28 21:50 作者: Dealing 時(shí)間: 2025-3-29 01:18 作者: 無(wú)思維能力 時(shí)間: 2025-3-29 06:08
Unsupervised Feature Selection Using Information-Theoretic Graph-Based Approach,ng of important features reduces the execution time and increases the predictive ability of the machine learning model. This paper presents a novel graph-based feature selection algorithm for unsupervised learning. Unlike many of the algorithms using correlation as a measure of dependency between fe作者: INTER 時(shí)間: 2025-3-29 10:56 作者: exhilaration 時(shí)間: 2025-3-29 15:17
Handling Seasonal Pattern and Prediction Using Fuzzy Time Series Model,em of seasonality. A few hybrid fuzzy time series models investigated the problem of forecasting in the presence of seasonal variation. But these techniques follow complex computational procedures. The aim of this present study is to develop a new fuzzy time series forecasting model that can process作者: 彈藥 時(shí)間: 2025-3-29 19:08
Automatic Classification of Fruits and Vegetables: A Texture-Based Approach,ect of the agricultural industry. It is quite challenging to automatically classify fruits and vegetables from digital images. The task of automatic classification becomes more difficult when the image is captured from a different viewing angle. This paper proposes a complete texture-based approach
