Advanced strategies on update mechanism of Sine Cosine Optimization Algorithm for feature selection in classification problems

[1]  Seyed Mohammad Mirjalili,et al.  Whale optimization approaches for wrapper feature selection , 2018, Appl. Soft Comput..

[2]  Seyed Mohammad Mirjalili,et al.  Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm , 2015, Knowl. Based Syst..

[3]  Mohamed H. Haggag,et al.  A novel chaotic salp swarm algorithm for global optimization and feature selection , 2018, Applied Intelligence.

[4]  Wei He,et al.  A Modified Sine-Cosine Algorithm Based on Neighborhood Search and Greedy Levy Mutation , 2018, Comput. Intell. Neurosci..

[5]  Xin-She Yang Harmony Search as a Metaheuristic Algorithm , 2009 .

[6]  Majdi M. Mafarja,et al.  Hybrid binary ant lion optimizer with rough set and approximate entropy reducts for feature selection , 2018, Soft Comput..

[7]  Ferat Sahin,et al.  A survey on feature selection methods , 2014, Comput. Electr. Eng..

[8]  Xin-She Yang,et al.  Firefly Algorithms for Multimodal Optimization , 2009, SAGA.

[9]  Diego Oliva,et al.  An improved Opposition-Based Sine Cosine Algorithm for global optimization , 2017, Expert Syst. Appl..

[10]  Hossam Faris,et al.  Binary dragonfly optimization for feature selection using time-varying transfer functions , 2018, Knowl. Based Syst..

[11]  Zong Woo Geem,et al.  A New Heuristic Optimization Algorithm: Harmony Search , 2001, Simul..

[12]  Andrew Lewis,et al.  The Whale Optimization Algorithm , 2016, Adv. Eng. Softw..

[13]  Manuel López-Ibáñez,et al.  Ant colony optimization , 2010, GECCO '10.

[14]  Nikola Bogunovic,et al.  A review of feature selection methods with applications , 2015, 2015 38th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO).

[15]  Luca Maria Gambardella,et al.  A survey on metaheuristics for stochastic combinatorial optimization , 2009, Natural Computing.

[16]  Qian Zhang,et al.  An efficient chaotic mutative moth-flame-inspired optimizer for global optimization tasks , 2019, Expert Syst. Appl..

[17]  Wen-Tsao Pan,et al.  A new Fruit Fly Optimization Algorithm: Taking the financial distress model as an example , 2012, Knowl. Based Syst..

[18]  Hossam Faris,et al.  Binary grasshopper optimisation algorithm approaches for feature selection problems , 2019, Expert Syst. Appl..

[19]  Andrew Lewis,et al.  Grasshopper Optimisation Algorithm: Theory and application , 2017, Adv. Eng. Softw..

[20]  Panos M. Pardalos,et al.  Simulated Annealing and Genetic Algorithms for the Facility Layout Problem: A Survey , 1997, Comput. Optim. Appl..

[21]  Yanfeng Wang,et al.  A modified invasive weed optimization with crossover operation , 2010, 2010 8th World Congress on Intelligent Control and Automation.

[22]  Caro Lucas,et al.  A novel numerical optimization algorithm inspired from weed colonization , 2006, Ecol. Informatics.

[23]  Shuihua Wang,et al.  Combining extreme learning machine with modified sine cosine algorithm for detection of pathological brain , 2018, Comput. Electr. Eng..

[24]  Dervis Karaboga,et al.  A comparative study of Artificial Bee Colony algorithm , 2009, Appl. Math. Comput..

[25]  J. Anuradha,et al.  A Survey on Particle Swarm Optimization in Feature Selection , 2011 .

[26]  Mohamed Elhoseny,et al.  Feature selection based on artificial bee colony and gradient boosting decision tree , 2019, Appl. Soft Comput..

[27]  M. Kubát An Introduction to Machine Learning , 2017, Springer International Publishing.

[28]  Uğur Yüzgeç,et al.  Performance comparison of differential evolution techniques on optimization of feeding profile for an industrial scale baker's yeast fermentation process. , 2010, ISA transactions.

[29]  Bernhard Sendhoff,et al.  Covariance Matrix Adaptation Revisited - The CMSA Evolution Strategy - , 2008, PPSN.

[30]  Caro Lucas,et al.  Imperialist competitive algorithm: An algorithm for optimization inspired by imperialistic competition , 2007, 2007 IEEE Congress on Evolutionary Computation.

[31]  D. Karaboga,et al.  On the performance of artificial bee colony (ABC) algorithm , 2008, Appl. Soft Comput..

[32]  Aboul Ella Hassanien,et al.  Feature selection via a novel chaotic crow search algorithm , 2017, Neural Computing and Applications.

[33]  Dinesh Gopalani,et al.  A Novel Swarm Intelligence Based Optimization Method: Harris' Hawk Optimization , 2018, ISDA.

[34]  Seyedmohsen Hosseini,et al.  A survey on the Imperialist Competitive Algorithm metaheuristic: Implementation in engineering domain and directions for future research , 2014, Appl. Soft Comput..

[35]  Qiang Shen,et al.  Computational Intelligence and Feature Selection - Rough and Fuzzy Approaches , 2008, IEEE Press series on computational intelligence.

[36]  Hossam Faris,et al.  Harris hawks optimization: Algorithm and applications , 2019, Future Gener. Comput. Syst..

[37]  Andrew Lewis,et al.  Grey Wolf Optimizer , 2014, Adv. Eng. Softw..

[38]  Aboul Ella Hassanien,et al.  Binary ant lion approaches for feature selection , 2016, Neurocomputing.

[39]  Asif Ekbal,et al.  Differential Evolution Based Feature Selection and Classifier Ensemble for Named Entity Recognition , 2012, COLING.

[40]  Satvir Singh,et al.  Butterfly optimization algorithm: a novel approach for global optimization , 2018, Soft Computing.

[41]  Ravi Kumar Jatoth,et al.  Hybridizing sine cosine algorithm with differential evolution for global optimization and object tracking , 2018, Appl. Soft Comput..

[42]  Charu C. Aggarwal,et al.  Educational and Software Resources for Data Classification , 2014, Data Classification: Algorithms and Applications.

[43]  Aboul Ella Hassanien,et al.  ASCA-PSO: Adaptive sine cosine optimization algorithm integrated with particle swarm for pairwise local sequence alignment , 2018, Expert Syst. Appl..

[44]  S. Baskar,et al.  Covariance matrix adaptation evolution strategy based design of centralized PID controller , 2010, Expert Syst. Appl..

[45]  Andries Petrus Engelbrecht,et al.  A memory guided sine cosine algorithm for global optimization , 2020, Eng. Appl. Artif. Intell..

[46]  E. Nowicki,et al.  A fast tabu search algorithm for the permutation flow-shop problem , 1996 .

[47]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[48]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[49]  Seyedali Mirjalili,et al.  SCA: A Sine Cosine Algorithm for solving optimization problems , 2016, Knowl. Based Syst..

[50]  Mesut Gündüz,et al.  Parameter Analysis on Fruit Fly Optimization Algorithm , 2014 .

[51]  Dan Simon,et al.  Blended biogeography-based optimization for constrained optimization , 2011, Eng. Appl. Artif. Intell..

[52]  Sarada Prasad Sarmah,et al.  Shuffled frog leaping algorithm and its application to 0/1 knapsack problem , 2014, Appl. Soft Comput..

[53]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[54]  Michel Gendreau,et al.  A Tabu Search Algorithm for a Routing and Container Loading Problem , 2006, Transp. Sci..

[55]  S. SreeRanjiniK.,et al.  Expert Systems With Applications , 2022 .

[56]  Seyed Mohammad Mirjalili How effective is the Grey Wolf optimizer in training multi-layer perceptrons , 2014, Applied Intelligence.

[57]  Ricardo Landa Becerra,et al.  Efficient evolutionary optimization through the use of a cultural algorithm , 2004 .

[58]  Huan Liu,et al.  Feature Selection for Clustering: A Review , 2018, Data Clustering: Algorithms and Applications.

[59]  Edgar Acuña,et al.  The Treatment of Missing Values and its Effect on Classifier Accuracy , 2004 .

[60]  Y. Ho,et al.  Simple Explanation of the No-Free-Lunch Theorem and Its Implications , 2002 .

[61]  Hossein Nezamabadi-pour,et al.  GSA: A Gravitational Search Algorithm , 2009, Inf. Sci..

[62]  Xin-She Yang,et al.  Firefly Algorithm, Lévy Flights and Global Optimization , 2010, SGAI Conf..

[63]  F. S. Gharehchopogh,et al.  Artificial gorilla troops optimizer: A new nature‐inspired metaheuristic algorithm for global optimization problems , 2021, Int. J. Intell. Syst..

[64]  Mengjie Zhang,et al.  Particle swarm optimisation for feature selection in classification: Novel initialisation and updating mechanisms , 2014, Appl. Soft Comput..

[65]  Patrick Siarry,et al.  A survey on optimization metaheuristics , 2013, Inf. Sci..

[66]  Ali Kaveh,et al.  Enhanced whale optimization algorithm for sizing optimization of skeletal structures , 2017 .

[67]  Shunmugapriya Palanisamy Artificial Bee Colony Approach for Optimizing Feature Selection , 2012 .

[68]  Seyed Mohammad Mirjalili,et al.  African vultures optimization algorithm: A new nature-inspired metaheuristic algorithm for global optimization problems , 2021, Computers & industrial engineering.

[69]  Muzaffar Eusuff,et al.  Shuffled frog-leaping algorithm: a memetic meta-heuristic for discrete optimization , 2006 .

[70]  A. Irawan,et al.  An Improved Sine Cosine Algorithm for Solving Optimization Problems , 2018, 2018 IEEE Conference on Systems, Process and Control (ICSPC).

[71]  David H. Wolpert,et al.  No free lunch theorems for optimization , 1997, IEEE Trans. Evol. Comput..

[72]  Adel Al-Jumaily,et al.  Differential evolution based feature subset selection , 2008, 2008 19th International Conference on Pattern Recognition.

[73]  Xin-She Yang,et al.  Cuckoo search: recent advances and applications , 2013, Neural Computing and Applications.

[74]  K. Chandrasekaran,et al.  Touring Ant colony Optimization technique for Optimal Power Flow incorporating thyristor controlled series compensator , 2009, 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC).

[75]  Isabelle Guyon,et al.  An Introduction to Variable and Feature Selection , 2003, J. Mach. Learn. Res..

[76]  Xin-She Yang,et al.  Cuckoo Search via Lévy flights , 2009, 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC).

[77]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[78]  Seyedali Mirjalili,et al.  Dragonfly algorithm: a new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems , 2015, Neural Computing and Applications.

[79]  Dan Simon,et al.  Biogeography-Based Optimization , 2022 .

[80]  Aboul Ella Hassanien,et al.  Binary grey wolf optimization approaches for feature selection , 2016, Neurocomputing.