標(biāo)題: Titlebook: Nature-Inspired Computation in Data Mining and Machine Learning; Xin-She Yang,Xing-Shi He Book 2020 Springer Nature Switzerland AG 2020 Na [打印本頁] 作者: 本義 時(shí)間: 2025-3-21 16:35
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書目名稱Nature-Inspired Computation in Data Mining and Machine Learning影響因子(影響力)學(xué)科排名
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書目名稱Nature-Inspired Computation in Data Mining and Machine Learning網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Nature-Inspired Computation in Data Mining and Machine Learning被引頻次
書目名稱Nature-Inspired Computation in Data Mining and Machine Learning被引頻次學(xué)科排名
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書目名稱Nature-Inspired Computation in Data Mining and Machine Learning讀者反饋
書目名稱Nature-Inspired Computation in Data Mining and Machine Learning讀者反饋學(xué)科排名
作者: Ambiguous 時(shí)間: 2025-3-21 20:13
https://doi.org/10.1007/978-3-030-28553-1Nature-inspired Algorithm; Computational Intelligence; Bio-inspired Computation; Bioinformatics; Data Mi作者: configuration 時(shí)間: 2025-3-22 02:02 作者: 粗俗人 時(shí)間: 2025-3-22 06:58
978-3-030-28555-5Springer Nature Switzerland AG 2020作者: palpitate 時(shí)間: 2025-3-22 10:33
Nature-Inspired Computation in Data Mining and Machine Learning978-3-030-28553-1Series ISSN 1860-949X Series E-ISSN 1860-9503 作者: lacrimal-gland 時(shí)間: 2025-3-22 15:51 作者: ARK 時(shí)間: 2025-3-22 18:46 作者: Lament 時(shí)間: 2025-3-23 00:22
1860-949X e learning.Discusses key directions in topics such as natureThis book reviews the latest developments in nature-inspired computation, with a focus on the cross-disciplinary applications in data mining and machine learning. Data mining, machine learning and nature-inspired computation are current hot作者: Cacophonous 時(shí)間: 2025-3-23 02:46
Book 2020ne learning. Data mining, machine learning and nature-inspired computation are current hot research topics due to their importance in both theory and practical applications. Adopting an application-focused approach, each chapter introduces a specific topic, with detailed descriptions of relevant alg作者: Gorilla 時(shí)間: 2025-3-23 07:47
,Algorithms for Optimization and?Machine Learning over Cloud, in exact way over the cloud environment. We also present these computations when the data is available in streaming fashion. Finally, we present related probabilistic generative models (PPCA and PLDA) and show comparative study between these algorithms with implemented experiments and related results.作者: 為現(xiàn)場 時(shí)間: 2025-3-23 09:54
An Improved Extreme Learning Machine Tuning by Flower Pollination Algorithm,s of the stated hybridization. Furthermore, it has been proved that our FPA-ELM approach is superior to other state-of-the-art algorithms from literature and that it can learn much faster weight coefficients compared to the other traditional learning methods, as well.作者: 符合規(guī)定 時(shí)間: 2025-3-23 14:42
3D Object Categorization in Cluttered Scene Using Deep Belief Network Architectures,shington RGBD dataset demonstrate the robustness of discriminative architecture which outperforms state-of-the-art. Also, we evaluate the performance of our approach on the real-world objects that are segmented from cluttered indoor scenes.作者: 頌揚(yáng)本人 時(shí)間: 2025-3-23 20:00 作者: 民間傳說 時(shí)間: 2025-3-24 00:05
A Comprehensive Review and Performance Analysis of Firefly Algorithm for Artificial Neural Networksas been efficiently used in neural network research to solve diversified applications. This chapter provides the detailed study about the applications and further, it discusses some of the major future challenges.作者: Platelet 時(shí)間: 2025-3-24 04:17 作者: 甜瓜 時(shí)間: 2025-3-24 10:10 作者: capsaicin 時(shí)間: 2025-3-24 11:21
Mohamed A. Tawhid,Abdelmonem M. Ibrahimy spectrum of electrons is much more complex than had originally been predicted: in many cases, there are several energy bands with different parameters. It has been found that the effective carrier mass, which had been assumed to be constant for a given material, depends on the carrier energy, temp作者: ARIA 時(shí)間: 2025-3-24 15:44
Adaptive Improved Flower Pollination Algorithm for Global Optimization,egant solutions. In this work, we introduced an improved adaptive version of the Flower Pollination Algorithm, which can dynamically change its parameter setting throughout the convergence process, as well as it keeps track of the best solutions. The effectiveness of the proposed approach is compare作者: Albumin 時(shí)間: 2025-3-24 19:18
,Algorithms for Optimization and?Machine Learning over Cloud,. Many relevant problems in these areas are computationally hard - generally modeled as optimization problems. These problems can be solved using exact algorithms or with the help of meta-heuristics - designed and inspired by natural computing. In this chapter, we consider two optimization problems 作者: 討厭 時(shí)間: 2025-3-25 03:12
Implementation of Machine Learning and Data Mining to Improve Cybersecurity and Limit Vulnerabilitirganizations and business turn to known network monitoring tools such as Wireshark, millions of people are still vulnerable because of lack of information pertaining to website behaviors and features that can amount to an attack. In fact, most of the attacks do not occur because of threat actors’ re作者: 懦夫 時(shí)間: 2025-3-25 04:51
,Comparative Analysis of Different Classifiers on Crisis-Related Tweets: An?Elaborate Study,mation about different events, often during mass crises. During any crisis, it is necessary to filter through a huge amount of tweets rapidly to extract incident related information. Different machine learning (ML) algorithms have been used to classify crisis related tweets from non crisis-related o作者: 天文臺(tái) 時(shí)間: 2025-3-25 09:51 作者: 鋼筆尖 時(shí)間: 2025-3-25 11:42 作者: 加入 時(shí)間: 2025-3-25 18:50 作者: Agronomy 時(shí)間: 2025-3-25 22:04
3D Object Categorization in Cluttered Scene Using Deep Belief Network Architectures,ing area. In this chapter, we extend our previous work [.] by classifying 3D object categories in real-world scenes. We extract geometric features from 3D point clouds using a 3D global descriptor called Viewpoint Feature Histogram (VFH) then we learn the extracted features with Deep Belief Networks作者: Increment 時(shí)間: 2025-3-26 00:34 作者: employor 時(shí)間: 2025-3-26 07:23 作者: 大酒杯 時(shí)間: 2025-3-26 10:04 作者: Misgiving 時(shí)間: 2025-3-26 15:49 作者: 連鎖,連串 時(shí)間: 2025-3-26 17:18
1860-949X -based prediction of diseases, and healthcare services. This book is both a valuable a reference resource and a practical guide for students, researchers and professionals in computer science, data and manageme978-3-030-28555-5978-3-030-28553-1Series ISSN 1860-949X Series E-ISSN 1860-9503 作者: 香料 時(shí)間: 2025-3-27 00:54 作者: PAGAN 時(shí)間: 2025-3-27 02:30 作者: 親愛 時(shí)間: 2025-3-27 07:22 作者: BACLE 時(shí)間: 2025-3-27 09:47
Janmenjoy Nayak,Bighnaraj Naik,Danilo Pelusi,A. Vamsi Krishna作者: entice 時(shí)間: 2025-3-27 17:34
Mohamed Alloghani,Dhiya Al-Jumeily,Abir Hussain,Panagiotis Liatsis,Ahmed J. Aljaaf作者: 騷動(dòng) 時(shí)間: 2025-3-27 21:15
Nature-Inspired Computation in Data Mining and Machine Learning作者: 難管 時(shí)間: 2025-3-27 23:07 作者: OATH 時(shí)間: 2025-3-28 04:59
Mohamed A. Tawhid,Abdelmonem M. Ibrahimo- gress is in the form of hundreds of publications, some of which re- port extremely refined and comprehensive investigations of semi- conducting materials. A scientist concerned with investigations or applications of semiconducting materials or devices cannot ignore these publica- tions because of作者: NATTY 時(shí)間: 2025-3-28 08:01 作者: MERIT 時(shí)間: 2025-3-28 12:51
,Comparative Analysis of Different Classifiers on Crisis-Related Tweets: An?Elaborate Study,tweets, (3) comparative analysis of different state-of-the-art ML algorithms (classifiers) which can be applied to categorize crisis-related tweets with a higher accuracy. The experiments have been done on six different crisis related datasets, each approximately consisting of 10,000 tweets. Analysi作者: 斥責(zé) 時(shí)間: 2025-3-28 17:00
Performance-Based Prediction of Chronic Kidney Disease Using Machine Learning for High-Risk Cardiovgistic regression (Ridge and Lasso), neural network (logistic and stochastic gradient descent), and support vector machine (Radial Basis Function and Polynomial) had very high accuracies and efficiency. With an efficiency of 93.4% and a classification accuracy of 91.7%, Polynomial Support Vector Mac作者: 拍下盜公款 時(shí)間: 2025-3-28 22:19 作者: expire 時(shí)間: 2025-3-29 00:59 作者: 安定 時(shí)間: 2025-3-29 06:42 作者: 刪減 時(shí)間: 2025-3-29 08:00 作者: 畫布 時(shí)間: 2025-3-29 14:41 作者: majestic 時(shí)間: 2025-3-29 17:16 作者: 壯觀的游行 時(shí)間: 2025-3-29 20:26 作者: discord 時(shí)間: 2025-3-30 02:46 作者: Entirety 時(shí)間: 2025-3-30 04:02
ricas, and to discuss the alternatives available to improve the existing and future water quality conditions in a cost-effective and timely manner, the Third World Centre for Water M- agement in Mexico, the Nat978-3-642-06354-1978-3-540-30444-9Series ISSN 1614-810X Series E-ISSN 2198-316X 作者: 沖擊力 時(shí)間: 2025-3-30 12:07
https://doi.org/10.1007/978-3-663-13129-8Für die L?sung jeder l?sbaren Aufgabe gibt es eine unendliche Anzahl von (abstrakten und konkreten) Algorithmen. Das folgende Problem illustriert, dass eine Aufgabe einfacher oder kompliziert, aber auch ?schlechter“ oder ?besser“ gel?st werden kann.作者: 倫理學(xué) 時(shí)間: 2025-3-30 13:08 作者: 強(qiáng)制性 時(shí)間: 2025-3-30 17:29
Conference proceedings 2025Formal Methods, ISoLA 2024, which took place in Crete, Greece, in October 2024.?..ISoLA 2024 provides a forum for developers, users, and researchers to discuss issues related to the adoption and use of rigorous tools and methods for the specification, analysis, verification, certification,?construct
