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Bi-LSTM-Based Deep Stacked Sequence-to-Sequence Autoencoder for Forecasting Solar Irradiation and Wind Speed

Computers, Materials & Continua 2023年第6期75卷 6375-6393页

作者： Neelam Mughees mujtaba hussain jaffery Abdullah Mughees Anam Mughees Krzysztof Ejsmont Department of Electrical and Computer Engineering COMSATS University IslamabadLahore Campus45550Pakistan School of Engineering and Technology National Textile UniversityFaisalabad37610Pakistan Department of Electrical Engineering Information Technology UniversityLahore54000Pakistan Department of Electrical Engineering GC UniversityFaisalabad38000Pakistan Faculty of Mechanical and Industrial Engineering Warsaw University of Technology02-524WarsawPoland

Wind and solar energy are two popular forms of renewable energy used in microgrids and facilitating the transition towards net-zero carbon emissions by ***,they are exceedingly unpredictable since they rely highly on weather and atmospheric *** microgrids,smart energy management systems,such as integrated demand response programs,are permanently established on a step-ahead basis,which means that accu-rate forecasting of wind speed and solar irradiance intervals is becoming increasingly crucial to the optimal operation and planning of *** this in mind,a novel“bidirectional long short-term memory network”(Bi-LSTM)-based,deep stacked,sequence-to-sequence autoencoder(S2SAE)forecasting model for predicting short-term solar irradiation and wind speed was developed and evaluated in *** create a deep stacked S2SAE prediction model,a deep Bi-LSTM-based encoder and decoder are stacked on top of one another to reduce the dimension of the input sequence,extract its features,and then reconstruct it to produce the *** of the proposed deep stacked S2SAE forecasting model were optimized using the Bayesian optimization ***,the forecasting performance of the proposed Bi-LSTM-based deep stacked S2SAE model was compared to three other deep,and shallow stacked S2SAEs,i.e.,the LSTM-based deep stacked S2SAE model,gated recurrent unit-based deep stacked S2SAE model,and Bi-LSTM-based shallow stacked S2SAE *** these models were also optimized and modeled in *** results simulated based on actual data confirmed that the proposed model outperformed the alternatives by achieving an accuracy of up to 99.7%,which evidenced the high reliability of the proposed forecasting.

关键词： Deep stacked autoencoder sequence to sequence autoencoder bidirectional long short-term memory network wind speed forecasting solar irradiation forecasting

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Adaptive Fuzzy Logic Controller for Harmonics Mitigation Using Particle Swarm Optimization

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Computers, Materials & Continua 2022年第6期71卷 4275-4293页

作者： Waleed Rafique Ayesha Khan Ahmad Almogren Jehangir Arshad Adnan Yousaf mujtaba hussain jaffery Ateeq Ur Rehman Muhammad Shafiq Department of Electrical&Computer Engineering COMSATS University Islamabad Lahore CampusLahore54000Pakistan Syed Babar Ali School of Science and Engineering Lahore University of Management SciencesLahore54000Pakistan Department of Computer Science College of Computer and Information SciencesKing Saud UniversityRiyadh11633Saudi Arabia Department of Electrical Engineering Superior UniversityLahore54000Pakistan Department of Electrical Engineering Government College UniversityLahore54000Pakistan Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

An excessive use of non-linear devices in industry results in current harmonics that degrades the power quality with an unfavorable effect on power system *** this research,a novel control techniquebased Hybrid-Active Power-Filter(HAPF)is implemented for reactive power compensation and harmonic current component for balanced load by improving the Power-Factor(PF)and Total–Hormonic Distortion(THD)and the performance of a *** work proposed a soft-computing technique based on Particle Swarm-Optimization(PSO)and Adaptive Fuzzy technique to avoid the phase delays caused by conventional control ***,the control algorithms are implemented for an instantaneous reactive and active current(Id-Iq)and power theory(Pq0)in *** prevent the degradation effect of disturbances on the system’s performance,PS0-PI is applied in the inner loop which generate a required dc ***,a comparative analysis of both techniques has been presented to evaluate and validate the performance under balanced load *** presented result concludes that the Adaptive Fuzzy PI controller performs better due to the non-linearity and robustness of the ***,the gains taken from a tuning of the PSO based PI controller optimized with Fuzzy Logic Controller(FLC)are optimal that will detect reactive power and harmonics much faster and *** proposed hybrid technique minimizes distortion by selecting appropriate switching pulses for VSI(Voltage Source Inverter),and thus the simulation has been taken in SIMULINK/*** proposed technique gives better tracking performance and robustness for reactive power compensation and harmonics *** a result of the comparison,it can be concluded that the PSO-basedAdaptive Fuzzy PI system produces accurate results with the lower THD and a power factor closer to unity than other techniques.

关键词： Harmonics compensation soft computing technique hybrid fuzzy PSO based PI controller HSAPF power quality

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Force Sensitive Resistors-Based Real-Time Posture Detection System Using Machine Learning Algorithms

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Computers, Materials & Continua 2023年第11期77卷 1795-1814页

作者： Arsal Javaid Areeb Abbas Jehangir Arshad Mohammad Khalid Imam Rahmani Sohaib Tahir Chauhdary mujtaba hussain jaffery Abdulbasid S.Banga Department of Electrical and Computer Engineering COMSATS University IslamabadLahore CampusLahore54000Pakistan College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia Department of Electrical and Computer Engineering College of EngineeringDhofar UniversitySalalah211Oman

To detect the improper sitting posture of a person sitting on a chair,a posture detection system using machine learning classification has been proposed in this *** addressed problem correlates to the third Sustainable Development Goal(SDG),ensuring healthy lives and promoting well-being for all ages,as specified by the World Health Organization(WHO).An improper sitting position can be fatal if one sits for a long time in the wrong position,and it can be dangerous for ulcers and lower spine *** novel study includes a practical implementation of a cushion consisting of a grid of 3×3 force-sensitive resistors(FSR)embedded to read the pressure of the person sitting on ***,the Body Mass Index(BMI)has been included to increase the resilience of the system across individual physical variances and to identify the incorrect postures(backward,front,left,and right-leaning)based on the five machine learning algorithms:ensemble boosted trees,ensemble bagged trees,ensemble subspace K-Nearest Neighbors(KNN),ensemble subspace discriminant,and ensemble RUSBoosted *** proposed arrangement is novel as existing works have only provided simulations without practical implementation,whereas we have implemented the proposed design in *** results validate the proposed sensor placements,and the machine learning(ML)model reaches a maximum accuracy of 99.99%,which considerably outperforms the existing *** proposed concept is valuable as it makes it easier for people in workplaces or even at individual household levels to work for long periods without suffering from severe harmful effects from poor posture.

关键词： Posture detection FSR sensor machine learning real-time KNN

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