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Binary Hybrid Artificial Hummingbird with flower pollination algorithm for Feature Selection in Parkinson’s Disease Diagnosis

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Journal of Bionic Engineering 2024年第2期21卷 1003-1021页

作者： Liuyan Feng Yongquan Zhou Qifang Luo College of Artificial Intelligence Guangxi University for NationalitiesNanning530006China Xiangsihu College of Guangxi University for Nationalities Nanning532100GuangxiChina Guangxi Key Laboratories of Hybrid Computation and IC Design Analysis Nanning530006China

Parkinson’s disease is a neurodegenerative disorder that inflicts irreversible damage on humans.Some experimental data regarding Parkinson’s patients are redundant and irrelevant,posing significant challenges for disease detection.Therefore,there is a need to devise an effective method for the selective extraction of disease-specific information,ensuring both accuracy and the utilization of fewer features.In this paper,a Binary Hybrid Artificial Hummingbird and flower pollination algorithm(FPA),called BFAHA,is proposed to solve the problem of Parkinson’s disease diagnosis based on speech signals.First,combining FPA with Artificial Hummingbird algorithm(AHA)can take advantage of the strong global exploration ability possessed by FPA to improve the disadvantages of AHA,such as premature convergence and easy falling into local optimum.Second,the Hemming distance is used to determine the difference between the other individuals in the population and the optimal individual after each iteration,if the difference is too significant,the cross-mutation strategy in the genetic algorithm(GA)is used to induce the population individuals to keep approaching the optimal individual in the random search process to speed up finding the optimal solution.Finally,an S-shaped function converts the improved algorithm into a binary version to suit the characteristics of the feature selection(FS)tasks.In this paper,10 high-dimensional datasets from UCI and the ASU are used to test the performance of BFAHA and apply it to Parkinson’s disease diagnosis.Compared with other state-of-the-art algorithms,BFAHA shows excellent competitiveness in both the test datasets and the classification problem,indicating that the algorithm proposed in this study has apparent advantages in the field of feature selection.

关键词： Artificial Hummingbird algorithm flower pollination algorithm Feature selection Parkinson’s disease Meta-heuristic

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A Differential Evolution flower pollination algorithm with Dynamic Switch Probability

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Chinese Journal of Electronics 2019年第4期28卷 737-747页

作者： LIU Jingsen LIU Li LI Yu Institute of Intelligent Network system Henan University College of Software Henan University Institute of Management Science and Engineering Henan University

For the shortcomings of the basic flower pollination algorithm, this paper proposes a differential evolution flower pollination algorithm with dynamic switch probability based on the Weibull distribution.This new algorithm improved the convergence rate and precision. The switch probability is improved by Weibull distribution function combined with the number of iterations. It can balance the relationship between the global pollination and the local pollination to improve the overall optimization performance of the algorithm.Random mutation operator is merged into the global pollination process to increase diversity of the population,enhance the ability of the algorithm’s global search and avoid premature convergence. In the process of local pollination, directed mutation and crossover operation of the differential evolution are incorporated, it makes the individual flower position update with the memory function, which can choose the direction of variation reasonably. The use of cross-operation can avoid new solutions crossing the boundary. Convergence rate is improved and the algorithm can approach the global optimal solution continuously. Theoretical analysis proved the convergence and time complexity of the improved algorithm. The simulation results based on the function optimization problem show that the improved algorithm has better performance of optimization, faster convergence speed and higher convergence accuracy.

关键词： flower pollination algorithm Dynamic switch probability Random mutation operator Differential evolution Optimization accuracy Convergence rate

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Feature Selection for Detecting ICMPv6-Based DDoS Attacks Using Binary flower pollination algorithm

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Computer Systems Science & Engineering 2023年第10期47卷 553-574页

作者： Adnan Hasan Bdair Aighuraibawi Selvakumar Manickam Rosni Abdullah Zaid Abdi Alkareem Alyasseri Ayman Khallel Dilovan Asaad Zebari Hussam Mohammed Jasim Mazin Mohammed Abed Zainb Hussein Arif National Advanced IPv6 Centre(NAv6) Universiti Sains MalaysiaPenang11800Malaysia Baghdad College of Economic Sciences University BaghdadIraq School of Computer Sciences Universiti Sains MalaysPenang11800Malaysia Information Technology Research and Development Center University of KufaNajafIraq College of Engineering University of Warith Al-AnbiyaaKarbalaIraq Faculty of Computing and Informatics Universiti Malaysia SabahSabahMalaysia Business Administration College of Administration and Financial SciencesImam Ja’afar Al-Sadiq UniversityBaghdad10001Iraq College of Computer Science and Information Technology University of AnbarRamadi AnbarIraq Department of Computer Science College of ScienceNawroz UniversityDuhok42001Kurdistan RegionIraq

Internet Protocol version 6(IPv6)is the latest version of IP that goal to host 3.4×10^(38)unique IP addresses of devices in the network.IPv6 has introduced new features like Neighbour Discovery Protocol(NDP)and Address Auto-configuration Scheme.IPv6 needed several protocols like the Address Auto-configuration Scheme and Internet Control Message Protocol(ICMPv6).IPv6 is vulnerable to numerous attacks like Denial of Service(DoS)and Distributed Denial of Service(DDoS)which is one of the most dangerous attacks executed through ICMPv6 messages that impose security and financial implications.Therefore,an Intrusion Detection System(IDS)is a monitoring system of the security of a network that detects suspicious activities and deals with amassive amount of data comprised of repetitive and inappropriate features which affect the detection rate.A feature selection(FS)technique helps to reduce the computation time and complexity by selecting the optimum subset of features.This paper proposes a method for detecting DDoS flooding attacks(FA)based on ICMPv6 messages using a Binary flower pollinationalgorithm(BFPA-FA).The proposed method(BFPA-FA)employs FS technology with a support vector machine(SVM)to identify the most relevant,influential features.Moreover,The ICMPv6-DDoS dataset was used to demonstrate the effectiveness of the proposed method through different attack scenarios.The results show that the proposed method BFPAFA achieved the best accuracy rate(97.96%)for the ICMPv6 DDoS detection with a reduced number of features(9)to half the total(19)features.The proven proposed method BFPA-FAis effective in the ICMPv6 DDoS attacks via IDS.

关键词： IPv6 ICMPv6 DDoS feature selection flower pollination algorithm anomaly detection

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A Novel flower pollination algorithm to Solve Load Frequency Control for a Hydro-Thermal Deregulated Power System

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Circuits and Systems 2016年第4期7卷 166-178页

作者： D. Lakshmi A. Peer Fathima Ranganath Muthu Department of Electrical and Electronics Engineering Sree Sastha Institute of Engineering and Technology Chennai India School of Electrical Engineering Vellore Institute of Technology Chennai India Department of Electrical and Electronics Engineering SSN College of Engineering Kalavakam Chennai India

Load frequency control plays a vital role in power system operation and control. LFC regulates the frequency of larger interconnected power systems and keeps the net interchange of power between the pool members at predetermined values for the corresponding changes in load demand. In this paper, the two-area, hydrothermal deregulated power system is considered with Redox Flow Batteries (RFB) in both the areas. RFB is an energy storage device, which converts electrical energy into chemical energy, that is used to meet the sudden requirement of real power load and hence very effective in reducing the peak shoots. With conventional proportional-integral (PI) controller, it is difficult to get the optimum solution. Hence, intelligent techniques are used to tune the PI controller of the LFC to improve the dynamic response. In the family of intelligent techniques, a recent nature inspired algorithm called the flower pollination algorithm (FPA) gives the global minima solution. The optimal value of the controller is determined by minimizing the ISE. The results show that the proposed FPA tuned PI controller improves the dynamic response of the deregulated system faster than the PI controller for different cases. The simulation is implemented in MATLAB environment.

关键词： Load Frequency Control Redox Flow Battery Proportional Integral Controller flower pollination algorithm

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Type-2 fuzzy logic applications designed for active parameter adaptation in metaheuristic algorithm for fuzzy fault-tolerant controller

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International Journal of Intelligent Computing and Cybernetics 2023年第2期16卷 198-222页

作者： Himanshukumar R.Patel Vipul A.Shah Department of Instrumentation and Control Dharmsinh Desai UniversityNadiadIndia

Purpose-In recent times,fuzzy logic is gaining more and more attention,and this is because of the capability of understanding the functioning of the system as per human knowledge-based system.The main contribution of the work is dynamically adapting the important parameters throughout the execution of the flower pollination algorithm(FPA)using concepts of fuzzy logic.By adapting the main parameters of the metaheuristics,the performance and accuracy of the metaheuristic have been improving in a varied range of applications.Design/methodology/approach-The fuzzy logic-based parameter adaptation in the FPA is proposed.In addition,type2 fuzzy logic is used to design fuzzy inference system for dynamic parameter adaptation in metaheuristics,which can help in eliminating uncertainty and hence offers an attractive improvement in dynamic parameter adaption in metaheuristic method,and,in reality,the effectiveness of the interval type2 fuzzy inference system(IT2 FIS)has shown to provide improved results as matched to type-1 fuzzy inference system(T1 FIS)in some latest work.Findings-One case study is considered for testing the proposed approach in a fault tolerant control problem without faults and with partial loss of effectiveness of main actuator fault with abrupt and incipient nature.For comparison between the type-1 fuzzy FPA and interval type-2 fuzzy FPA is presented using statitical analysis which validates the advantages of the interval type2 fuzzy FPA.The statistical Z-test is presented for comparison of efficiency between two fuzzy variants of the FPA optimization method.Originality/value-The main contribution of the work is a dynamical adaptation of the important parameters throughout the execution of the flower pollination optimization algorithm using concepts of type2 fuzzy logic.By adapting the main parameters of the metaheuristics,the performance and accuracy of the metaheuristic have been improving in a varied range of applications.

关键词： Interval Type-2 fuzzy logic flower pollination algorithm Fuzzy fault tolerant controller

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Selective Harmonics Elimination Technique for Artificial Bee Colony Implementation

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Computer Systems Science & Engineering 2023年第6期45卷 2721-2740页

作者： T.DeepikaVinothini R.Karthigaivel J.BarsanaBanu Department of Electrical and Electronics Engineering Velammal College of Engineering and TechnologyMaduraiIndia Department of Electrical and Electronics Engineering PSNA College of Engineering and TechnologyDindigulIndia Department of Electrical and Electronics Engineering SBM College of Engineering and TechnologyDindigulIndia

In this research,an Artificial Bee Colony(ABC)algorithm based Selective Harmonics Elimination(SHE)technique is used as a pulse generator in a reduced switch fifteen level inverter that receives input from a PV system.Pulse width modulation based on Selective Harmonics Elimination is mostly used to suppress lower-order harmonics.A high gain DC-DC-SEPIC converter keeps the photovoltaic(PV)panel’s output voltage constant.The Grey Wolf Optimization(GWO)filter removes far more Photovoltaic panel energy from the sunlight frame.To eliminate voltage harmonics,this unique inverter architecture employs a multi-carrier duty cycle,a high-frequency modulation approach.The proposed ABC harmonics elimination approach is compared to SHE strategies based on Particle Swarm Optimization(PSO)and flower pollination algorithm(FPA).The suggested system’s performance is simulated and measured using the MATLAB simulation tool.The proposed ABC approach has a THD level of 4.86%,which is better than the PSO and FPA methods.

关键词： Artificial bee colony photovoltaic flower pollination algorithm multi-carrier

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A Machine Learning Based algorithm to Process Partial Shading Effects in PV Arrays

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Computers, Materials & Continua 2021年第7期68卷 29-43页

作者： Kamran Sadiq Awan Tahir Mahmood Mohammad Shorfuzzaman Rashid Ali Raja Majid Mehmood Department of Electrical Engineering University of Engineering and TechnologyTaxila47080Pakistan Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia School of Intelligent Mechatronics Engineering Sejong UniversityKorea Department of Information and Communication Technology School of Electrical and Computer EngineeringXiamen University MalaysiaSepang43900Malaysia

Solar energy is a widely used type of renewable energy.Photovoltaic arrays are used to harvest solar energy.The major goal,in harvesting the maximum possible power,is to operate the system at its maximum power point(MPP).If the irradiation conditions are uniform,the P-V curve of the PV array has only one peak that is called its MPP.But when the irradiation conditions are non-uniform,the P-V curve has multiple peaks.Each peak represents an MPP for a specific irradiation condition.The highest of all the peaks is called Global Maximum Power Point(GMPP).Under uniform irradiation conditions,there is zero or no partial shading.But the changing irradiance causes a shading effect which is called Partial Shading.Many conventional and soft computing techniques have been in use to harvest solar energy.These techniques perform well under uniform and weak shading conditions but fail when shading conditions are strong.In this paper,a new method is proposed which uses Machine Learning based algorithm called Opposition-Based-Learning(OBL)to deal with partial shading conditions.Simulation studies on different cases of partial shading have proven this technique effective in attaining MPP.

关键词： Maximum power point tracking flower pollination algorithm opposition-based-learning flower pollination algorithm hybridized with opposition based learning

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flower pollination Heuristics for Parameter Estimation of Electromagnetic Plane Waves

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Computers, Materials & Continua 2021年第8期68卷 2529-2543页

作者： Sadiq Akbar Muhammad Asif Zahoor Raja Naveed Ishtiaq Chaudhary Fawad Zaman Hani Alquhayz Department of Electronics University of PeshawarPeshawar25120Pakistan Future Technology Research Center National Yunlin University of Science and TechnologyDouliou64002Taiwan Department of Electrical Engineering International Islamic UniversityIslamabad44000Pakistan Department of Electrical Engineering COMSATS University IslamabadIslamabad44000Pakistan Department of Computer Science and Information College of Science in ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia

For the last few decades,the parameter estimation of electromagnetic plane waves i.e.,far field sources,impinging on antenna array geometries has attracted a lot of researchers due to their use in radar,sonar and under water acoustic environments.In this work,nature inspired heuristics based on the flower pollination algorithm(FPA)is designed for the estimation problem of amplitude and direction of arrival of far field sources impinging on uniform linear array(ULA).Using the approximation in mean squared error sense,a fitness function of the problem is developed and the strength of the FPA is utilized for optimization of the cost function representing scenarios for various number of sources non-coherent located in the far field.The worth of the proposed FPA based nature inspired computing heuristic is established through assessment studies on fitness,histograms,cumulative distribution function and box plots analysis.The other worthy perks of the proposed scheme include simplicity of concept,ease in the implementation,extendibility and wide range of applicability to solve complex optimization problems.These salient features make the proposed approach as an attractive alternative to be exploited for solving different parameter estimation problems arising in nonlinear systems,power signal modelling,image processing and fault diagnosis.

关键词： Direction of arrival flower pollination algorithm plane waves parameter estimation

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flower pollination Heuristics for Nonlinear Active Noise Control Systems

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Computers, Materials & Continua 2021年第4期67卷 815-834页

作者： Wasim Ullah Khan Yigang He Muhammad Asif Zahoor Raja Naveed Ishtiaq Chaudhary Zeshan Aslam Khan Syed Muslim Shah School of Electrical Engineering and Automation Wuhan UniversityWuhan430072China Future Technology Research Center National Yunlin University of Science and TechnologyYunlin64002Taiwan Department of Electrical Engineering International Islamic UniversityIslamabadPakistan Department of Electrical Engineering Capital University of Science and TechnologyIslamabadPakistan

In this paper,a novel design of the flower pollination algorithm is presented for model identification problems in nonlinear active noise control systems.The recently introduced flower pollination based heuristics is implemented to minimize the mean squared error based merit/cost function representing the scenarios of active noise control system with linear/nonlinear and primary/secondary paths based on the sinusoidal signal,random and complex random signals as noise interferences.The flower pollination heuristics based active noise controllers are formulated through exploitation of nonlinear filtering with Volterra series.The comparative study on statistical observations in terms of accuracy,convergence and complexity measures demonstrates that the proposed meta-heuristic of flower pollination algorithm is reliable,accurate,stable as well as robust for active noise control system.The accuracy of the proposed nature inspired computing of flower pollination is in good agreement with the state of the art counterpart solvers based on variants of genetic algorithms,particle swarm optimization,backtracking search optimization algorithm,fireworks optimization algorithm along with their memetic combination with local search methodologies.Moreover,the central tendency and variation based statistical indices further validate the consistency and reliability of the proposed scheme mimic the mathematical model for the process of flower pollination systems.

关键词： Active noise control computational heuristics volterra filtering flower pollination algorithm

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Application of metaheuristic algorithms in interval type-2 fractional order fuzzy TID controller for nonlinear level control process under actuator and system component faults

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International Journal of Intelligent Computing and Cybernetics 2021年第1期14卷 33-53页

作者： Himanshukumar R.Patel Vipul A.Shah Instrumentation and Control Engineering Department Faculty of TechnologyDharmsinh Desai UniversityNadiadIndia

Purpose–The two-tank level control system is one of the real-world’s second-order system(SOS)widely used as the process control in industries.It is normally operated under the Proportional integral and derivative(PID)feedback control loop.The conventional PID controller performance degrades significantly in the existence of modeling uncertainty,faults and process disturbances.To overcome these limitations,the paper suggests an interval type-2 fuzzy logic based Tilt-Integral-Derivative Controller(IT2TID)which is modified structure of PID controller.Design/methodology/approach–In this paper,an optimization IT2TID controller design for the conical,noninteracting level control system is presented.Regarding to modern optimization context,the flower pollination algorithm(FPA),among the most coherent population-based metaheuristic optimization techniques is applied to search for the appropriate IT2FTID’s and IT2FPID’s parameters.The proposed FPA-based IT2FTID/IT2FPID design framework is considered as the constrained optimization problem.System responses obtained by the IT2FTID controller designed by the FPA will be differentiated with those acquired by the IT2FPID controller also designed by the FPA.Findings–As the results,it was found that the IT2FTID can provide the very satisfactory tracking and regulating responses of the conical two-tank noninteracting level control system superior as compared to IT2FPID significantly under the actuator and system component faults.Additionally,statistical Z-test carried out for both the controllers and an effectiveness of the proposed IT2FTID controller is proven as compared to IT2FPID and existing passive fault tolerant controller in recent literature.Originality/value–Application of new metaheuristic algorithm to optimize interval type-2 fractional order TID controller for nonlinear level control system with two type of faults.Also,proposed method will compare with other method and statistical analysis will be presented.

关键词： Actuator fault flower pollination algorithm Interval type-2 fuzzy logic System component fault TID control

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