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3rd International Conference on computing, Communication, Control and Automation (ICCUBEA)

作者： Mandaogade, Nitin N. Ingole, Prashant V. Thakare, Sneha GHRCEM Dept EXTC Amravati Maharashtra India PRMITR IT Dept Amravati Maharashtra India

ISBN: (纸本)9781538640081

Circuit fault diagnosis is an important area for electronic manufacturing industries. For critical applications, it is desired to design & develop the system that will detect the fault appearing condition by analyzing various circuit parameters. It is proposed to develop the fault detection and diagnosis system which analyzes circuit parameters like supply current and output voltage of circuit under test (CUT). From these parameters it is possible to identify the deviation in performance of the circuit. The circuit under test is H Bridge Inverter which converts the input DC voltage to AC voltage. Analog circuit fault detection and diagnosis system based on embedded board is achieved. A real time embedded system with ATmega16 microcontroller is developed due to which real time data extraction is possible. Back Propagation neural network algorithm with embedded system is applied to that system. Real-time data collection, analog circuit fault detection and location are designed as the basic functions of fault detection and diagnosis system.

关键词： CUT Circuit Parameters Fault Diagnosis soft computing technique

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Realization of 5-bus System Using soft computing technique for Flexible Alternating Current Transmission System (FACTS) Devices 17

Realization of 5-bus System Using Soft Computing Technique f...

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17th IEEE International Conference on Environment and Electrical Engineering (IEEE EEEIC) / 1st IEEE Industrial and Commercial Power Systems Europe Conference (IEEE I and CPS Europe)

作者： Ashokrao, Zade Ankit Machhindra, Pachagade Ruchi Padmanaban, Sanjeevikumar Bhaskar, Mahajan Sagar Martirano, Luigi Leonowicz, Zbigniew Jagadambha Coll Engn & Technol Dept Elect Engn Yavatmal India Univ Johannesburg Dept Elect & Elect Engn Johannesburg South Africa Sapienza Univ Rome Dept Elect Engn Rome Italy Wroclaw Univ Technol Fac Elect Engn Wroclaw Poland

ISBN: (纸本)9781538639177

Total transfer capability analysis of power system is currently a critical issue in both planning & operating of systems. These issues mainly occur due to increase in area and interchanges among utilities. To reduce the flows in heavily loaded lines, Flexible Alternating Current Transmission System (FACTS) devices is used, this results in increased transfer capability, improve stability of the network, low system losses, and fulfill contractual required by controlling the power flows in the network. To achieve parameters FACTS devices are placed optimally and is done with the help of reduction of total system reactive power loss sensitivity indices analysis method and real power flow performance index sensitivity indices analysis method. Thyristor-Control-Series-Capacitor (TCSC) is used as a FACTS device in the proposed sensitivity analysis method. To decide priority of line for placing TCSC, soft computing technique "Fuzzy logic method" is employed. The performance evaluation of proposed sensitivity analysis methods is done using electrical IEEE-5 bus system. The sensitivity indices are programmed using Matrix Laboratory.

关键词： soft computing technique Sensitivity Analysis Method Power System Stability FACTS TCSC Fuzzy

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Fault Detection and Diagnosis of Analog Circuit Using soft computing technique

Fault Detection and Diagnosis of Analog Circuit Using Soft C...

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International Conference on computing, Communication, Control and Automation

作者： Nitin N. Mandaogade Prashant V. Ingole Sneha Thakare Dept. of EXTC GHRCEM Amravati Maharashtra India IT Dept. PRMITR Badnera Amravati Maharashtra India

Circuit fault diagnosis is an important area for electronic manufacturing industries. For critical applications, it is desired to design & develop the system that will detect the fault appearing condition by analyzing various circuit parameters. It is proposed to develop the fault detection and diagnosis system which analyzes circuit parameters like supply current and output voltage of circuit under test (CUT). From these parameters it is possible to identify the deviation in performance of the circuit. The circuit under test is H Bridge Inverter which converts the input DC voltage to AC voltage. Analog circuit fault detection and diagnosis system based on embedded board is achieved. A real time embedded system with ATmega 16 microcontroller is developed due to which real time data extraction is possible. Back Propagation neural network algorithm with embedded system is applied to that system. Real-time data collection, analog circuit fault detection and location are designed as the basic functions of fault detection and diagnosis system.

关键词： CUT Circuit Parameters Fault Diagnosis soft computing technique

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Parameter Extraction and Performance Evaluation of Glazed PVT Module for Indian Climatic Conditions Based on soft computing technique

Parameter Extraction and Performance Evaluation of Glazed PV...

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International Conference on 21st Century Energy Needs - Materials, Systems and Applications (ICTFCEN)

作者： Singh, Sonveer Dash, Amit Kumar Kumar, Neeraj Agrawal, Sanjay CMS Govt Girls Polytech Meerut Uttar Pradesh India Bharat Inst Technol Meerut Uttar Pradesh India SV Subharti Univ SITE Meerut Uttar Pradesh India IGNOU Sch Engn New Delhi India

ISBN: (纸本)9781509035649

The work is carried out in two ways;one is the overall exergy efficiency of glazed photovoltaic thermal (PVT) module which is optimized with soft computing technique. Evolutionary algorithm is used as a computing techniques in this work. The overall exergy efficiency is considered as the objective function while the optimization is carried out. Secondly, the annual performance of optimized (different parameter like the depth and length of the channel, thickness of tedlar etc.) glazed PVT module has been evaluated. This evaluation has been carried out in four different cities of India (New Delhi, Srinagar, Jodhpur and Bangalore). Here the four weather conditions have been considered like- Clear days, Hazy Days, Hazy and cloudy days and Cloudy days. Overall exergy efficiency for New Delhi, Bangalore, Srinagar and Jodhpur has been observed for a year, for each weather condition. There are improvements in overall annual exergy efficiency, annual thermal gain and annual exergy gain of the proposed glazed PVT module for New Delhi, Jodhpur, Srinagar and Bangalore and the range of improvement in monthly overall exergy efficiency is 5.8 % to 14.70 % than the model given in literature.

关键词： Performance evaluation PVT module Parameter Extraction soft computing technique

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Application of soft computing techniques in the optimization of 3D-printed piezoresistive sensors

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SENSORS AND ACTUATORS A-PHYSICAL 2025年 385卷

作者： Razbin, Milad Vahdani, Mostafa Moshizi, Sajad Abolpour Bagherzadeh, Roohollah Proust, Gwenaelle Ravindran, Anil Withana, Anusha Asadnia, Mohsen Wu, Shuying Univ Sydney Sch Aerosp Mech & Mechatron Engn Sydney NSW 2006 Australia Macquarie Univ Sch Engn Sydney NSW 2109 Australia Amirkabir Univ Technol Inst Adv Text Mat & Technol Adv Fibrous Mat LAB Tehran *** Iran Univ Sydney Sch Civil Engn Sydney NSW 2006 Australia Univ Sydney Sydney Mfg Hub Sydney NSW 2006 Australia Univ Sydney Sch Comp Sci Sydney NSW 2006 Australia

Fused Deposition Modeling (FDM) stands out as one of the most accessible additive manufacturing methods, offering a wide variety of compatible materials and adaptable structural configurations for sensor fabrication. Printing parameters are critical especially to control anisotropy and printing qualities, which significantly influences the electromechanical behavior of sensors. Therefore, it is essential to identify the optimal set of parameters to achieve desired properties. This study employs a hybrid soft computing approach, combining artificial neural networks and genetic algorithms, to model and optimize the gauge factor of the 3D-printed piezoresistive sensors fabricated using conductive thermoplastic polyurethane. Experiments were conducted using response surface methodology, and key control variables, such as layer height, printing speed, shell count, infill angle, and overlap percentage, were systematically varied. By using soft computing techniques, it was revealed that a specific set of printing parameters, i.e., a layer height of 0.4 mm, a printing speed of 40 mm/s, five shells, an infill angle of 90o, and overlap of 15 %, resulted in sensors with a maximum gauge factor of 12.5. The potential application of the optimized piezoresistive sensor for monitoring shoulder loads in educational backpacks is also highlighted.

关键词： Fused deposition modeling Thermoplastic polyurethane Piezoresistive sensors soft computing technique

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Comparison of Neural Network techniques and Multi-Linear Regression to Predict Properties and Classify Pepper Seeds

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JOURNAL OF FOOD PROCESS ENGINEERING 2025年第3期48卷

作者： Yildirim, Demet Cevher, Elcin Yesiloglu Black Sea Agr Res Inst Soil & Water Resources Dept Agr Irrigat & Land Reclamat Samsun Turkiye Univ Ondokuz Mayis Fac Agr Dept Agr Machinery & Technol Engn Samsun Turkiye

Pepper seed quality is determined using the mechanical and physical properties through artificial neural networks (ANNs) to enable accurate and timely agricultural planning. The objective of this study is to develop a model that provides simple, precise, rapid, and cost-effective predictions based on thousand-grain weight, porosity, and various classifications for pepper seeds. To achieve this, three different models-artificial neural networks (ANN), radial basis function (RBF), and multiple linear regression analysis (MLR) were employed to estimate thousand-grain weight and porosity. The best-selected model was then used to classify 12 different pepper seed varieties. This applied model's performance was evaluated using the determination coefficient (R2), the root mean square error (RMSE), the mean relative percentage absolute error (MRPE), and the mean square error (MSE). A comparison of the ANN model results indicated that the input parameters-width, length, thickness, and bulk density-provided the optimal prediction model concerning R2, RMSE, MRPE, and MSE. For the testing dataset, the ANN model achieved values ranging from 0.88 to 0.92 for R2, 0.276 to 0.016 for RMSE, 1.647 to 0.232 for MRPE, and 0.138-0.008 for MSE using 5-8-1 and 8-10-1 network structures, respectively. These selected models can be used as a neurocomputing-based approach to predict the mechanical and physical properties of pepper seeds, assisting in variety classification and genotype prediction.

关键词： best model multi-linear regression pepper seeds various and genotypes soft computing technique

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Ensemble Bagging Model for Predicting Flexural Strength of Geopolymer Concrete

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INTERNATIONAL JOURNAL OF COMPUTATIONAL METHODS 2025年第5期22卷

作者： Onal, Yasemin Turhal, Umit Cigdem Ozodabas, Aylin Bilecik Seyh Edebali Univ Engn Fac Elect & Elect Engn Dept TR-11210 Bilecik Turkiye Bilecik Seyh Edebali Univ Engn Fac Civil Engn Dept TR-11210 Bilecik Turkiye

Waste materials, such as fly ash and lime mortar, are used in the concrete industry to create an environmentally friendly environment. However, since the experimental studies will take time, it is necessary to predict the flexural strength (FS) and properties of Geopolymer concrete (GPC) using ensemble Learning (EL) algorithms in order to shorten the experimental work process and save money and time. In this study, a new ensemble the Bagging prediction model using gradient boosting regressor estimator is proposed to predict the FS of GPC using lime mortar. The performance of the proposed model was evaluated using the performance metrics R-2, RMSE, MSE, MAE, and MAPE. The proposed model was compared using the individual learning algorithms and validated using k-fold cross-validation technique. From the SHAP plot obtained using the best proposed EL model BGR, ICE, and PDP analysis, it is seen that the blast furnace slag content has the most significant effect on the FS of GPC.

关键词： Ensemble learning model bagging regression flexural strength soft computing technique

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Experimental investigation and prediction of strength development of GGBFS-, LFS- and SCBA-based green concrete using soft computing techniques

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ARABIAN JOURNAL OF GEOSCIENCES 2021年第23期14卷 1-15页

作者： Rani, Kavita Suthar, Manju Sihag, Parveen Boora, Amardeep Dr BR Ambedkar Natl Inst Technol Dept Civil Engn Jalandhar 144011 Punjab India Chandigarh Univ Dept Civil Engn Mohali 140413 Punjab India Jaypee Univ Informat Technol Dept Civil Engn Waknaghat 173234 Himachal Prades India

The present research article is focusing on the utilization of ground granulated blast furnace slag (GGBFS), ladle furnace slag (LFS) and sugarcane bagasse ash (SCBA) as the partial substitution of ordinary Portland cement (OPC) in concrete mix in order to create a sustainable environment and enhance the engineering performance. The primary purpose of the study is to predict the optimum percentage of different additives in varying proportions, i.e. individually and in a combined manner also to construct a sustainable rigid pavement. Therefore, accurate estimation of strength evaluation is required to minimize the effort. In the current investigation, different modeling analysis techniques have been attempted with different soft computing tools, namely random forest (RF), random tree (RT), M5P, reduced-error pruning (REP) tree and linear regression (LR) to estimate the compressive strength of the concrete using the experimental data. In the present study, all the mentioned additives were added in the concrete mix as the replacement of OPC up to 35%. On the basis of the findings, it was observed that 20% of all the additives in individual form might be used as the partial substitute of OPC. While, in a combined form, concrete mix having 5% GGBFS, 10% LFS and 15% of SCBA was showing the optimum strength value. However, it was also observed that the greater percentage of all the additives can be utilized with an increment in the curing time period. RF approach was found most permissible approach to predict the strength value for green concrete as it was exhibiting higher value of coefficient of correlation, low value of mean absolute error and the root mean square error as revealed by outcomes of the models and statistical assessments methods. Sensitivity analysis is carried out and found that the curing time in days is the utmost effective input variable for estimating the compressive strength of concrete using this data set.

关键词： soft computing technique Ground granulated blast furnace slag Ladle furnace slag Sugarcane bagasse ash Concrete

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Order Reduction of LTI Systems Using Balanced Truncation and Particle Swarm Optimization Algorithm

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2023年第8期42卷 4506-4552页

作者： Duddeti, Bala Bhaskar Naskar, Asim Kumar Subhashini, K. R. Natl Inst Technol Rourkela Elect Engn Dept Rourkela India

This paper presents a novel hybrid model reduction method to simplify large-scale continuous-time single-input-single-output and multi-input-multi-output dynamic systems using the advantages of the balanced truncation method and the particle swarm optimization (PSO) algorithm. The balanced truncation method obtains the reduced model denominator coefficients to ensure stability. The PSO algorithm minimizes the integral square error between the step responses of the original system and the reduced model as much as possible. It leads to the optimal numerator coefficients. The advantage of the proposed approach is that, for optimizing reduced model numerator coefficients, the search space boundaries of the PSO algorithm are not entirely random. They are selected using the balanced truncated reduced model numerator. So, the suggested method avoids two significant problems with evolutionary algorithms: the arbitrary choice of search space and the longer simulation time. Four power system models and four numerical examples from the literature are considered to assess the effectiveness of the proposed reduction method. The step responses and Bode diagrams for the higher-order system and its corresponding reduced models are displayed. For comparison, statistics are tabulated based on the rise time, the settling time, the peak overshoot, the integral square error, and the root-mean-square error. The proposed method ensures stability and other features of the higher-order system in the reduced model. The performance measure values and the time domain characteristics demonstrate the ability and effectiveness of the proposed approach. All the case studies use a MATLAB simulation environment.

关键词： Large-scale dynamic systems Model order reduction Particle swarm optimization Performance indices soft computing technique Balanced truncation method SISO and MIMO systems

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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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