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Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur’s entropy by Bhandari, A.K., Singh, V.K, Kumar, A., Singh, G.K.

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Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

“…Clustering technique is able to find hidden patterns and to extract useful information from huge data. Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

“…However, the complexity of the kmedoid based algorithms in general is more than the complexity of the k-means based algorithms. …”
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A web-based implementation of k-means algorithms by Lee, Quan

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Fuzzy rank cluster top k Euclidean distance and triangle based algorithm for magnetic field indoor positioning system by Bundak, Caceja Elyca, Abd Rahman, Mohd Amiruddin, Abdul Karim, Muhammad Khalis, Osman, Nurul Huda

“…However, the problem of using the KNN algorithm is the fixed K value does not guarantee accurate estimation at every position. …”
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Cluster Analysis of Data Points using Partitioning and Probabilistic Model-based Algorithms by Raheem, Ajiboye Adeleke, Hauwau, Isah-Kebbe, O., Oladele Tinuke

“…Experiments were conducted using k-means, k-medoids and EM-algorithm. The study implements each algorithm using RapidMiner Software and the results generated was validated for correctness in accordance to the concept of external criteria method. …”
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Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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Autonomous and deterministic supervised fuzzy clustering by Lim, K.M., Loo, C.K., Lim, W.S.

“…The results obtained show that the model that uses the global k-means clustering algorithm 1 has higher accuracy when compared to a model that uses the k-means clustering algorithm. …”
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Document clustering based on firefly algorithm by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

“…Document clustering is widely used in Information Retrieval however, existing clustering techniques suffer from local optima problem in determining the k number of clusters.Various efforts have been put to address such drawback and this includes the utilization of swarm-based algorithms such as particle swarm optimization and Ant Colony Optimization.This study explores the adaptation of another swarm algorithm which is the Firefly Algorithm (FA) in text clustering.We present two variants of FA; Weight- based Firefly Algorithm (WFA) and Weight-based Firefly Algorithm II (WFAII).The difference between the two algorithms is that the WFAII, includes a more restricted condition in determining members of a cluster.The proposed FA methods are later evaluated using the 20Newsgroups dataset.Experimental results on the quality of clustering between the two FA variants are presented and are later compared against the one produced by particle swarm optimization, K-means and the hybrid of FA and -K-means. …”
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Jogging activity recognition using k-NN algorithm by Afifah Ismail

“…The k-NN algorithm is a simple and easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems. …”
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Optimization of k-Nearest Neighbour to categorize Indonesian’s news articles by Ihsan, Afdhalul, Rainarli, Ednawati

“…If we use the appropriate features, then the k-NN will be a reliable algorithm. …”
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Classification of credit card holder behavior using K Nearest Neighbor algorithm / Ahmad Faris Rahimi by Rahimi, Ahmad Faris

“…The second one is to develop prototype for classification of credit cardholder behavior based on k Nearest Neighbors Algorithm. The third one is to evaluate the accuracy of the k Nearest Neighbors algorithm in the classification credit card holder behavior. …”
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Evidence-based diagnostic algorithm for visceral leishmaniasis in Bangladesh by Salam, Md. Abdus, Huda, M. Mamun, Khan, Md. Gulam Musawwir, Shomik, Mohammad Sohel, Mondal, Dinesh

“…Evidence-based diagnostic algorithm is highly recommended for the visceral leishmaniasis (VL). …”
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Detection of the spread of Covid-19 in Indonesia using K-Means Clustering Algorithm / Mohammad Yazdi Pusadan ... [et al.] by Pusadan, Mohammad Yazdi, Rabbani, Mohammad Abied, Ardiansyah, Rizka, Ngemba, Hajra Rasmita

“…In this study, the method used is K-Means to perform clustering based on area grouping. …”
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Facial expression type recognition using K-Nearest Neighbor algorithm / Norhafizah Saffian by Saffian, Norhafizah

“…Based on this calculation, the accuracy of this algorithm is 93% using the k values of 5. …”
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Confidentiality Based Data Classification Using Sematic-K-NN Algorithm in Cloud Virtual Enviroment by Ali, Munwar

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An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title by Khalaf, Emad Taha

“…The enhanced method combines three transformation methods for analyzing the iris image and extracting its local features. It uses a weighted K-means clustering algorithm based on the improved FA to optimize the initial clustering centers of K-means algorithm, known as Weighted K-means clustering-Improved Firefly Algorithm (WKIFA). …”
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Ant system-based feature set partitioning algorithm for K-NN and LDA ensembles construction by Abdullah, , Ku-Mahamud, Ku Ruhana

“…Combination of several classifiers has been very useful in improving the prediction accuracy and in most situations multiple classifiers perform better than single classifier.However not all combining approaches are successful at producing multiple classifiers with good classification accuracy because there is no standard resolution in constructing diverse and accurate classifier ensemble.This paper proposes ant system-based feature set partitioning algorithm in constructing k-nearest neighbor (k-NN) and linear discriminant analysis (LDA) ensembles. …”
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k- Nearest Neighbor Algorithm For Improving Accuracy In Clutter Based Location Estimation Of Wireless Nodes by Muhammad Mansoor Alam, Mazliham Mohd Su'ud, Patrice Boursier, Shahrulniza Musa

“…This research is focusing on the precise location estimation of mobile node by using k - nearest neighbor algorithm (k-NN). It is based on our previous research findings in which we divided the geographical area into thirteen clutters/terrains based on the behavior of radio waves. …”

Efficient k-coverage scheduling algorithms for wireless sensor networks / Ahmed Abdullah Saleh Al-Shalabi by Saleh Al-Shalabi, Abdullah

“…The third demonstrated algorithm is a power aware k-coverage algorithm for WSNs with adjustable sensing range. …”
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