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International Conference of Information and Communication Technology (ICICT)

作者： Alhakeem, Zaineb M. Ali, Ramzy S. Univ Basrah Dept Elect Engn Basra Iraq

ISBN: (纸本)9781450366434

In Brain Computer Interface (BCI), the brain signals are used to perform some commands or actions in a computer. Brain signals are recorded using many methods. Electroencephalogram (EEG) is one of the non-invasive methods. EEG signals are recorded using multiple channels. Selection methods are used to choose the most relevant and powerful signals. Usually Meta-heuristic algorithms are used for selection. Meta-heuristic algorithms depends on random generated population of solutions for the objective function. Because of the randomness, there is always a chance to select zero as a solution. Zero in EEG channels selection means no channel is chosen to extract its signal features. This situation is not practical, the selection process should be repeated whenever a zero solution appears. The repetition will reduce the algorithm speed. This paper introduces a fast channel selection algorithm using crow search algorithm (CSA). CSA is used to select the best channels offline. Using no-zero channel condition to fasten the algorithm. Our results show that CSA with no-zero channels condition is better than Genetic algorithm (GA). Although CSA and GA results are almost have the same accuracy, but CSA with no-zero condition is faster.

关键词： Brain Computer Interface crow search algorithm Electroencephalography EEG Fast selection Genetic algorithm Motor Imagery

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crow search algorithm-Optimized Cascade Controller in a Multi-Area Thermal Wind Integrated System and Its Real-Time Validation

ELECTRICA

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ELECTRICA 2023年第3期23卷 429-+页

作者： Babu, Naladi Ram Chiranjeevi, Tirumalasetty Saha, Arindita Bhagat, Sanjeev Kumar Gupta, Umesh Kumar Vais, Ram Ishwar Aditya Engn Coll Dept Elect & Elect Engn Surampalem Andhra Pradesh India Jawaharlal Nehru Technol Univ Kakinda Andhra Pradesh India Rajkiya Engn Coll Sonbhadra Dept Elect Engn Markundi UP India Regent Educ & Res Fdn Grp Inst Dept Elect Engn Kolkata India NIT Silchar Dept Elect Engn Silchar Assam India

This article explores the load frequency control (LFC) problem for manifold areas and sources under conventional situations. An attempt has been made to demonstrate the solicitation of a real-time simulation laboratory for the LFC studies of three thermal area systems. Thermal systems are integrated with renewable like wind systems in area-1, 2 respectively. A novel ancillary controller termed by cascade tilt integral-proportional integral derivative (TI-PID) is suggested and is augmented by crow search algorithm. The superiority of TI-PID controller is tested and found to be better with PID and tilt integral derivative (TID) controller. Moreover, the obtained responses with hybrid peak area-integral square error are compared with ISE, and it shows better responses over ISE. Further, the responses with alternating current-high-voltage direct- current system improve system dynamics over wind-thermal and thermal systems. Furthermore, sensitivity analysis suggests that the TID with filter controller considerations attained at nominal circumstances are vigorous.

关键词： Load frequency control cascade controller hybrid peak area-integral square error crow search algorithm wind system

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Heart Disease Classification using crow search algorithm 5

Heart Disease Classification using Crow Search Algorithm

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5th International Conference on Smart Electronics and Communication, ICOSEC 2024

作者： Maragatharajan, M. Naveen, P. Nirmala, E. Vit Bhopal University School of Computing Science and Engineering Madhya Pradesh Kothrikalan India Kpr Institute of Engineering and Technology Department of Electrical and Electronics Engineering Tamilnadu Coimbatore India

ISBN: (纸本)9798331504403

This work introduces cutting-edge research to predict heart diseases. This application designed for accurate and personalized assessment of cardiovascular health. This work aims to provide an overall understanding of an individual's heart health by integrating these multifaceted data points. This work utilizes a vast dataset to establish correlations and patterns, enabling it to categorize users into specific risk groups or diagnose potential heart diseases. Through continuous learning and adaptation, the work refines its predictive capabilities, ensuring that it remains up-to-date with emerging medical knowledge. The work not only assists in early detection of cardiovascular issues but also aids in personalized risk assessment, guiding users towards lifestyle modifications and preventive measures based on their unique health profiles. This innovative solution holds the potential to revolutionize the field of cardiovascular health assessment, offering a proactive and data-driven approach to identify and manage heart diseases efficiently. This study considered two well-known machine learning models namely Extreme learning machine algorithms (ELM) and crow search algorithm (CSA). The collected dataset consists of 10000 samples. We have attained 92.5% accuracy with the data set. The incorporation of machine learning models ensures scalability, adaptability, and precision, making it a valuable tool for both healthcare professionals and individuals striving for proactive heart care. © 2024 IEEE.

关键词： Accuracy crow search algorithm Data preprocessing Extreme learning machine algorithm Feature selection Heart diseases

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Train the Multi-Layer Perceptrons Based on crow search algorithm 1

Train the Multi-Layer Perceptrons Based on Crow Search Algor...

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1st International Conference Information Technology to Enhance E-Learning and other Application, IT-ELA 2020

作者： Khamees, Muntadher Ahmed, Wasan S. Abbas, Saad Q. Diyala University Dept. Computer Sciences Diyala Iraq Bilad Al Rafidain University College Dept. Medical Instruments Engineering Techniques Diyala Iraq

ISBN: (纸本)9781728182339

This paper presents a new approach for training the Multi-Layer Perceptron (MLP) based on the crow search algorithm (CSA) optimization algorithm. The main objective of this approach is to reduce the error to its minimum level and increase the rate of the classification. The benchmark of the proposed approach implementation achieved using more than one standard datasets for classification to ensure the quality of the result, and the performance also compared with other optimization algorithms such as Particle Swarm optimization (PSO), Genetic algorithm (GA), and Ant Colony optimization (ACO). The outcomes indicated that the crow search algorithm was the best since it produces the highest accuracy rate and solves the optimization problem efficiently. © 2020 IEEE.

关键词： crow search algorithm Multi-Layer Perceptron optimization problem

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A Novel Technique Based on crow search algorithm to Solve Optimal Control Problem of a Single-Link Rigid Robotic Manipulator 2

A Novel Technique Based on Crow Search Algorithm to Solve Op...

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2nd International Conference on Power Electronics and Energy, ICPEE 2023

作者： Sahu, Venkata Satya Durga Manohar Samal, Padarbinda Panigrahi, Chinmoy Kumar School of Electrical Engineering Kalinga Institute of Industrial Technology Deemed to Be University Bhubaneswar India

ISBN: (纸本)9781665470582

This study shows how Meta-heuristic optimization programming may be implemented to solve constrained optimal control problems. With a single-link rigid manipulator (SLM) model as an example, the proposed crow search algorithm (CSA) is contrasted with the differential evolution algorithm (DE), whale optimization algorithm (WOA), and particle swarm optimization (PSO) in terms of performance index, which has demonstrated the notable outcomes on another algorithm. © 2023 IEEE.

关键词： crow search algorithm optimal control problem single-link rigid manipulator

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Computing the Load Margin of Power Systems Using crow search algorithm 7th

Computing the Load Margin of Power Systems Using Crow Search...

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7th International Conference on Advances in Control and Optimization of Dynamical Systems, ACODS 2022

作者： Bento, Murilo E.C. Federal University of Rio de Janeiro RJ Rio de Janeiro21941909 Brazil

Power system operation centers require knowledge of the load level where the system may present instability characteristics. It is common practice to calculate the load margin where the system can collapse in voltage respecting a direction of load growth. However, the increase in load can also cause low damped oscillation modes to appear and cause small-signal stability problems of power systems. This research proposes a crow search algorithm-based method to calculate the load margin of power systems considering small-signal stability and voltage stability requirements. To solve the problem of good initial conditions for the search problem, the Sine Cosine algorithm was used. The proposed method was evaluated in the IEEE 39-bus system and the results achieved show the effectiveness of the method in determining the load margins quickly. © 2022 Elsevier B.V.. All rights reserved.

关键词： crow search algorithm Dynamic Security Assessment Power System Stability Sine Cosine algorithm Small-Signal Stability Smart Grid Voltage Stability

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A ranking-based fuzzy adaptive hybrid crow search algorithm for combined heat and power economic dispatch

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EXPERT SYSTEMS WITH APPLICATIONS 2022年第0期197卷

作者： Ramachandran, Murugan Mirjalili, Seyedali Ramalingam, Mohan Malli Gnanakkan, Christober Asir Rajan Charles Parvathysankar, Deiva Sundari Sundaram, Arunachalam KCG Coll Technol Dept Elect & Elect Engn Chennai 600097 Tamil Nadu India Torrens Univ Australia Ctr Artificial Intelligence Res & Optimizat Brisbane Qld Australia Meenakshi Coll Engn Dept Elect & Elect Engn Chennai 600078 Tamil Nadu India Pondicherry Engn Coll Dept Elect & Elect Engn Pondicherry 605014 India Jubail Ind Coll Dept Elect & Elect Engn Technol Al Jubail 31961 Jubail Ind City 31961 Saudi Arabia Yonsei Univ Yonsei Frontier Lab Seoul South Korea

This paper attempts to obtain optimal generation scheduling for Combined Heat and Power Economic Dispatch (CHPED) problems and seeking a possible solution for the global optimization of test systems. As such, a Fuzzy adaptive Ranking-based crow search algorithm (FRCSA) is amalgamated with modified Artificial Bee Colony (ABC). The proposed algorithm (FRCSA-ABC) has been integrated with three mechanisms in order to achieve competitive results effectively. The first mechanism uses the Fuzzy logic Inference System (FIS) to tune dynamically the parameters of flight length (fl) and awareness probability (CAP) of each crow. The second mechanism emerges from a natural phenomenon known as proximate optimality principle (POP) which reveals that better individuals will often have beneficial information and more probabilities to select and guide other individuals. This observation leads to the feasibility-based Ranking crow search algorithm (RCSA) which generates a new food source from the chosen higher rankings of parent food sources. The third mechanism integrates the two modified global search phases of ABC with a local search phase of FRCSA to ensure promising performance. During the evaluation process, this mechanism investigates the aging level of the individual's best solution (p(best)) in order to choose an appropriate search phase in FRCSA and two modified phases of ABC. The performance of the algorithm is tested on four CHPED test systems, 23 well-known benchmark functions, and test suit of CEC2017. The results obtained are compared with its variants as well as with existing different approaches to validate its optimal search efficiency. Further, non-parametric statistical tests such as pair-wise and multiple comparisons tests are adapted to establish the supremacy of the FRCSA-ABC. The seminal aspect of this intended algorithm is that it can achieve cost-effectiveness conforming to meticulous global convergence.

关键词： Combined heat and power economic dispatch crow search algorithm Artificial bee colony algorithm Adaptive ranking selection Fuzzy logic Sine-Cosine

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Value aided optimal load shedding accounting voltage stability consideration employing crow search algorithm with modification based on Lampinen's criterion

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APPLIED SOFT COMPUTING 2023年 143卷

作者： Singh, Pushpendra Arya, Rajesh Titare, L. S. Purey, Pradeep Arya, L. D. Rajkiya Engn Coll Banda Dept Elect Engn Banda 210201 UP India Medi Caps Univ Dept Elect Engn Indore 453331 MP India Govt Engn Coll Dept Elect Engn Ujjain 456010 MP India Maharaja Ranjit Singh Coll Profess Sci Dept Elect Indore 452001 MP India

This paper describes a novel load-shedding strategy that assures adequate voltage stability margin in post-load-shedding conditions. Minimum numbers of buses are selected for load shedding based on the incremental voltage of the load buses. An objective function has been formed that is to be minimized based on inequality constraints on load bus voltage and line flow. This objective function is the weighted sum of the slope of the PV-curve of the weakest bus, transmission losses, and the total load shed amount, which has been normalized with respect to the pre-load shed condition. A modified crow search algorithm (CSA) has been used to obtain optimal load shed. The developed methodology has been implemented on standard IEEE 14 and 25-bus test systems, and comparisons based on statistical inferences have been carried out with the Sine-Cosine, Jaya, and Self-adaptive differential evolution (SaDE) algorithms. & COPY;2023 Elsevier B.V. All rights reserved.

关键词： Load shedding Voltage stability Slope of PV-curve Optimization crow search algorithm Load flow

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Security-constrained optimal placement of PMUs using crow search algorithm

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APPLIED SOFT COMPUTING 2022年 128卷

作者： Johnson, Teena Moger, Tukaram Natl Inst Technol Karnataka Dept Elect & Elect Engn Mangalore 575025 Karnataka India

For precise power system monitoring, a major focus is on involvement of the latest technology based on phasor measurement units (PMUs). As the sole system monitor, state estimator plays an important role in the security of power system operations. Optimal placement of PMUs (OPP) with numerical observability ensures reliable state estimation. For economical and efficient utilization, there is a need to optimize the placement of PMUs in the power system network. A new approach called crow search algorithm (CSA) devised by others, has been used to solve an OPP problem. The performance of this new approach is compared to the dominant method for an optimization problem - binary integer linear programming (BILP). Comparison studies have also been carried out with particle swarm optimization (PSO) method. The major constraints such as topological, numerical observability conditions with and without zero-injection buses (ZIBs) are considered. Contingencies and limitation of measurement channels in a PMU device are also incorporated as constraints. The main advantage of using the CSA is that it provides multiple location sets for same optimal number of PMUs (optimal number same as obtained by BILP). While BILP method provides only one set of locations for the optimal number of PMUs obtained. This becomes advantageous in planning stage for power engineers for placing PMUs. Test systems considered for the case studies are of varied sizes such as IEEE 14-bus, IEEE 30-bus, IEEE 57-bus and 72-bus practical equivalent system of Indian southern region power grid. (C) 2022 Elsevier B.V. All rights reserved.

关键词： crow search algorithm Numerical observability Phasor measurement unit Power systems Optimal placement

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Modeling and global optimization of biodiesel synthesis using hybrid response surface methodology-crow search algorithm: Case study of papaya seed waste oil utilization

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ENVIRONMENTAL PROGRESS & SUSTAINABLE ENERGY 2021年第6期40卷 e13689-e13689页

作者： Hossain, S. M. Zakir Sultana, N. Taher, S. Khan, A. Razzak, S. A. Hossain, M. M. Univ Bahrain Dept Chem Engn Zallaq Bahrain Imam Abdulrahman Bin Faisal Univ Dept Comp Sci Dammam Saudi Arabia King Fahd Univ Petr & Minerals Dept Chem Engn Dhahran Saudi Arabia

Biodiesel is potential renewable and clean energy, which can be produced form wide range of waste materials. This study employs a hybrid response surface methodology (RSM) and crow search algorithm (CSA) as novel tool for global optimization of transesterification reaction parameters to maximize biodiesel synthesis from papaya seed-derived waste oil. Catalyst (NaOH) dose, methanol to oil molar ratio (M:O), and reaction time were considered independent factors, while biodiesel yield was taken as a dependent variable. The experimentally produced biodiesel was characterized by gas chromatography-mass spectrometry analysis. The experiments were developed based on RSM with Box-Behnken design matrix, which was subsequently used for modeling, optimization and model validation. Initially, a quadratic regression model was developed following RSM technique, correlating the transesterification reaction parameters and biodiesel yield. Afterward, the CSA coupled with RSM approach was employed to assess the global optimization. A highest biodiesel yield of 99.48% was attained with a catalyst (NaOH) dose of 0.5 wt%, M:O of 8.5:1 at a reaction time of 40 min. The results acquired by RSM-CSA were also compared with the results achieved by desirability function-based optimization technique. Further, the optimal set for maximizing biodiesel yield was validated experimentally with an error margin of 2.0%. These observations indicate that the hybrid RSM-CSA is an efficient and economic approach to optimize the process conditions for biodiesel production from alternative sources.

关键词： crow search algorithm modeling optimization papaya biodiesel response surface methodology

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