Control Design Research Articles

Safe formation control of multiple unmanned aerial vehicles: control design and safety-stability analysis

Safe formation control of multiple unmanned aerial vehicles: control design and safety-stability analysis

The Effect of Technological Pedagogical Content Knowledge (TPACK) on Rural Area Students’ English Writing

This research was conducted to examine the impact of the Technological Pedagogical Content Knowledge (TPACK) and Direct Learning (DL) model on the learning outcomes of students in rural areas concerning English descriptive text composition. The models introduced a meaningful learning experience within conventional classroom settings, enabling students to connect prior knowledge with new information in creating innovative ideas. TPACK model played an essential role in the educational system, facilitating teachers in integrating technological, pedagogical, and content knowledge throughout the instructional process. Therefore, students became more engaged, active, and enthusiastic participants in their learning. An authentic experimental and control group design was carried out in two parallel classes at a senior high school. Meanwhile, ANOVA Factorial (2-way ANOVA) was used to analyze the data. The results showed that the learning outcomes of TPACK were significantly different from those of the DL group. Therefore, TPACK substantially affected the learning outcomes of students in writing English descriptive text. This research reported the valuable contribution of the model in equipping future teachers with the knowledge necessary to integrate content, learning theories, teaching models, methods, and technology into their instructional practices.

Brain, behavior, cognition, and physical health in first-onset adolescent anorexia nervosa: The BRAVE Study design and cohort profile

Background Anorexia nervosa is a severe psychiatric disorder with a heterogeneous course with one of the highest rates of morbidity and mortality of all psychiatric disorders. Little is known about factors that predict both course and treatment outcomes of this disorder. The BRAVE Study is a longitudinal first-onset anorexia nervosa cohort study focusing on four topics of interest in girls only: (1) behavior, (2) neurobiology, (3) cognitive functions, and (4) physical health. Objective The goal of this paper is to introduce the BRAVE Study. The primary aim of the BRAVE Study is to identify predictors of treatment response in a large sample of 12-to-22-year-old females with first-onset typical or atypical anorexia nervosa. The second aim is to longitudinally investigate the association between clinically significant changes in eating disorder symptoms with the underlying behavioral, neurobiological, cognitive and physical health changes. The results of this study will allow us to develop more precise treatment strategies in order to provide more optimal treatment. Methods and analysis The BRAVE Study implements a longitudinal case-control design. Study recruitment was designed within a collaborative network of 16 Dutch mental health organizations, each with expertise in the diagnosis and treatment of patients with anorexia nervosa. After obtaining informed consent, assessments were performed at baseline and one-year follow-up. Patients with anorexia nervosa received treatment as usual. The primary outcome measures at one year are restoration of weight and a reduction of eating disorder symptomatology. Predictive measures include neurobiological, cognitive, behavioral and physical health measures. Sample description In the BRAVE Study 79 girls with anorexia nervosa and 75 typically developing girls were included between May 2017 and October 2021. This period of time partially overlapped with the COVID-19 pandemic. 72% of the girls with anorexia nervosa and 88% of the typically developing girls also completed measurements at follow-up. The mean time between data collections points was 13 months. The groups were comparable in education level of their mothers, neurodevelopmental disorders, and ethnical background. The girls with anorexia nervosa were slightly younger than the typically developing girls. Conclusion The BRAVE Study aligns with one of the most important study priorities in the field of anorexia nervosa by examining (i) predictors of treatment response and (ii) investigating how symptoms with eating disorder symptoms track with changes in neurobiological, cognitive, behavorial and physical health functioning. Moreover, the study is innovative by its longitunal case control design, relatively large study sample and broad selection of measures.

Integrating a blended discovery learning model with a bioenial website to empower science process skills and scientific attitude

This study aims to determine; 1) the effect of integrating blended discovery learning with a bioenial website to empower Science Process Skills (SPS) of grade X students on the material of environmental change and preservation and 2) the effect of integrating blended discovery learning with a bioenial website to empower the scientific attitude of grade X students on the material of environmental change. The research method used a quasi experiment with a quantitative approach. The research design used posttest only control group design to measure SPS and pretest-posttest nonequivalent control group design to measure scientific attitudes. The population in this study were X grade students of SMA Negeri A Sukoharjon the 2022/2023 academic year. The samples of this study were X2 class as experimental class 1 as many as 36 students, X4 as experimental class 2 as many as 36 students, and X5 as control class as many as 36 students. The sampling technique used was cluster random sampling. Data collection questionnaire (scientific attitude), observation (SPS, scientific attitude, syntax implementation), and documentation. Data analysis technique used ANOVA hypothesis test for SPS and ANCOVA for scientific attitude. The ANOVA test results showed the effect of integrating blended discovery learning with the bioenial website to empower SPS. The results of further testing with LSD show that Blended Discovery Learning is a treatment that is significantly different among the three class groups. The ANCOVA test results show that there is no effect of integrating blended discovery learning with the bioenial website to empower scientific attitudes

Efficacy of Celecoxib and Naproxen Sodium After Non-Surgical Extraction of Permanent Teeth: A Randomized Control Study

Objective: To compare the level of pain relief that two NSAID salts offer following a simple closed tooth extraction technique, as well as to assess patient adherence to the prescribed dosage schedule. Methodology: This Randomized Control Design study was conducted at Islamabad medical & dental college, from 2018-2019. 150 patients made up the sample, who were split into two equal groups using a computerized lottery system: the experimental group and the control group. Following tooth extraction under local anesthesia, participants in the experimental group were told to take one 200 mg tablet of celecoxib orally for two days, while the control group was administered two 550 mg tablets of Naproxen Sodium orally twice a day. The standard Visual Analogue Scale (VAS) was used to assess post-extraction pain after 24 and 48 hours. Patients' adherence was verified by having them fill out a Performa form by phone call after 48 hours. After collection of Data, analysis was done with the help of SPSS version 21.0. Results: After tooth extraction, both medications were similarly effective in reducing pain, although participants adhered to the OD dose of celecoxib substantially more than the BD dose of naproxen sodium. Conclusion: There was statistically insignificant difference in pain relief provided by Celecoxib and Naproxen Sodium after 24 and 48 hours of single tooth extraction.

Sand screen selection by sand retention test: a review of factors affecting sand control design

AbstractThe installation of sand screens in open-hole completions in the wellbore is crucial for managing sand production. The main reason for using standalone screens in open-hole completions is their relatively reduced operational complexity compared to other sand control technologies. However, directly applying the screen to the bottom of the hole can lead to an incorrect screen type selection, resulting in an unreliable sand control method. To address this issue, a sand retention test is conducted to evaluate the performance of a standalone screen before field installation. Nevertheless, current sand retention test setups encounter several challenges. These include difficulties in identifying minimum retention requirements, interpreting results in the context of field conditions, and replicating field-specific parameters. The existing sand retention test introduces uncertainties, such as inaccurately replicating field requirements, inconsistent selection of wetting fluids, flow rates, and channel formation, leading to variations in the choice of the optimal screen using this test. In response to these challenges, this study aims to review the sand retention test and propose an improved sand retention method to overcome these problems. The focus of this article is to provide an in-depth analysis of previous sand retention test setups, their contributions to characterizing sand screens, and the parameters utilized in determining test outcomes. Additionally, this review outlines a procedure to investigate the impact of different particle sizes on screen erosion. Key findings emphasize the importance of using high-quality materials, proper screen design to resist damage and erosion, achieving acceptable natural packing behind the screen, and considering factors such as geology, wellbore conditions, and installation techniques. The analysis reveals that a high quantity of finer and poorly sorted sand increases sand production. The study recommends performing a sand pack test closer to reservoir conditions for better evaluation. Premium sand screens demonstrate the highest retention capacity, followed by metal mesh and wire-wrapped screens. Additionally, geotextiles show potential for enhancing sand retention, and screen design affects erosion resistance and service life.

Adaptive Neural Control for a Class of Random Fractional-Order Multi-Agent Systems with Markov Jump Parameters and Full State Constraints

Based on an adaptive neural control scheme, this paper investigates the consensus problem of random Markov jump multi-agent systems with full state constraints. Each agent is described by the fractional-order random nonlinear uncertain system driven by random differential equations, where the random noise is the second-order stationary stochastic process. First, in order to deal with the unknown functions with Markov jump parameters, a radial basis function neural network (RBFNN) structure is introduced to achieve approximation. Second, for the purpose of keeping the agents’ states from violating the constraint boundary, the tan-type barrier Lyapunov function is employed. By using the stochastic stability theory and adopting the backstepping technique, a novel adaptive neural control design method is presented. Furthermore, to cope with the differential explosion problem in the design course, the extended state observer (ESO) is developed instead of neural network (NN) approximation or command filtering techniques. Finally, the exponentially noise-to-state stability in the mean square is analyzed rigorously by the Lyapunov method, which guarantees the consensus of the considered multi-agent systems and all the agents’ outputs are bounded in probability. Two simulation examples are provided to verify the effectiveness of the suggested control strategy.

Improving frequency regulation ability for a wind-thermal power system by multi-objective optimized sliding mode control design

Enhancing the frequency response ability of the wind-thermal coordinated load frequency control system is an effective means to maintain the stability of the grid frequency and improve the flexibility of the new power system. Thus, this paper designs a cascaded extended state observer sliding mode control (CE-SMC) method based on the osprey-dung beetle fusion optimization algorithm and applies it to the wind-thermal coordinated system to improve the frequency regulation performance of the system. Firstly, cascaded extended state observers are utilized to accurately estimate the combined effects of parameter uncertainties and internal and external disturbances in the system and compensated by sliding mode controller in real time, which helps the system to achieve fast frequency regulation. Secondly, the osprey-dung beetle fusion optimization algorithm is employed to optimize the parameters of CE-SMC. Moreover, a multi-objective function including the frequency regulation performance, thermal power unit output smoothness, carbon emission and economy is constructed to guide the power system to operate at the utopian point of flexibility, economy and low carbon. The control scheme effectively combines the features of fast frequency response, robust immunity and accurate parameter tuning. Finally, simulations are carried out in different load disturbances and various wind power penetration rates. Results show that the CE-SMC scheme can effectively improve the frequency response ability of the system while taking into account energy saving and emission reduction. Compared with integral sliding mode control, the frequency regulation performance is improved by 20.99 %, the output stability of thermal power unit is improved by 19.31 %, the power generation cost is reduced by 1.88 % and the carbon emission is reduced by 2.16 % in single load perturbation. As such, the CE-SMC algorithm provides a practical reference for the flexible, low-carbon and economic operation of new power system.

Smoke diffusion mechanism and mitigation design for fire accidents in a tunnel-groove structure of a large hydropower station

In this study, field tests and numerical simulations were conducted to investigate the smoke diffusion mechanism and mitigation design for a fire accident occurring in a special hybrid structure, i.e., the tunnel-groove structure (TGS) of a large hydropower station. It is found that the characteristics of the smoke spread in the TGS include the smoke temperature attenuation, incomplete chimney effect and smoke entrainment. The combustion of the polyurethane flame-retardant material is controllable and extinguishes immediately after the fire source is removed. However, there is a fire risk in a relatively closed space under the conditions of strong winds, especially at the connection port with the external environment, due to the wind tunnel and chimney effects, which result in rapid smoke diffusions. During the fire accident, the smoke first fills in the entire tunnel (89 m long), then propagates upward along the groove, and finally reaches the dam top (115 m above the tunnel) in 10 s. The heat release rate (HRR) was determined as approximately 50 MW and the maximum velocity of the smoke spread along the dam surface could reach 10 m/s. As a result, nearly no time was available for the workers in the groove to evacuate when the fire accident occurred. Sensitivity analyses were further conducted to study the effects of different parameters, such as the HRR, the air inflow velocity and the radial gate opening, on the smoke diffusion in the TGS. A horizontal smoke plate (HSP) was proposed for the temporary smoke control to prevent life from losses due to the smoke diffusion in the TGS. The safe and dangerous zones near the dam surface were identified by analyzing the characteristics of the smoke temperature and visibility. It was finally concluded that the HSP can mitigate the smoke and heat along the groove. The results from this study may serve as a useful reference for the smoke control design in the TGS or other similar structure configurations.

Observer-based control for plasma glucose regulation in type 1 diabetes mellitus patients with unknown input delay.

This article introduces an observer-based control strategy tailored for regulating plasma glucose in type 1 diabetes mellitus patients, addressing challenges like unknown time-varying delays and meal disturbances. This control strategy is based on an extended Bergman minimal model, a nonlinear glucose-insulin model to encompass unknown inputs, such as unplanned meals, exercise disturbances, or delays. The primary contribution lies in the design of an observer-based state feedback control in the presence of unknown long delays, which seeks to support and enhance the performance of the traditional artificial pancreas by considering realistic scenarios. The observer and control gains for the observer-based control are computed through linear matrix inequalities formulated from Lyapunov conditions that guarantee closed-loop stability. This design deploys a soft and gentle dynamic response, similar to a natural pancreas, despite meal disturbances and input delays. Numerical tests demonstrate the scheme's effectiveness in glycemic level regulation and hypoglycemic episode avoidance.

A new control method for leader–follower consensus problem of uncertain constrained nonlinear multi-agent systems

The design of Adaptive Fuzzy Sliding-Mode Control (AFSMC) is discussed in this study for the distributed leader–follower consensus problem of nonlinear uncertain multi-agent systems with input and state constraints. Avoiding the critical circumstances related to the violation of input and state constraints is an important issue in the design of consensus control systems. The limitations of existing adaptive consensus controllers developed for full-state constrained systems motivated the present novel method without restrictive structural assumptions. To convert the original problem to an unconstrained consensus control problem, the proposed control system uses a barrier function-based state transformation method and the input-state linearization methodology. As a result, each agent’s adaptive fuzzy sliding-mode control input, which consists of a fuzzy system and a robust term, is constructed based on the derived representation of the system dynamics. The fuzzy system is used to approximate the dynamic equations of the agent, its neighbors, and maybe the leader in each local feedback control law structure, and the robust term is designed to compensate for the fuzzy approximation error. The magnitudes of the robust terms and the output vectors of the fuzzy systems are also determined using the proposed adaptation laws. The second Lyapunov theorem and Barbalat’s lemma are used to verify the closed-loop system’s asymptotic stability. The effectuality of the proposed methodology is confirmed by numerical simulations for several Autonomous Underwater Vehicles (AUVs). Simulation results show that by means of the proposed AFSMC, the leader–follower consensus is achieved without state constraint violation and performance degradation.

Efektivitas Layanan Bimbingan Klasikal dengan Metode Diskusi untuk Meningkatkan Motivasi Belajar Siswa

The problem that will be raised in this study is whether there is an effective classical guidance service with the discussion method to increase student motivation at SMA N 3 Pati. Based on the problem formulation, the purpose of this study was to find out how effective the discussion method classical guidance service was to increase student motivation at SMA N 3 Pati. This type of research is experimental. This research method uses a true experimental design with a posttest-only control design technique. The population in this study is class XI MIPA 1, XI MIPA 2, XI MIPA 3, XI MIPA 4, XI MIPA 5, XI MIPA 6, XI MIPA 7, XI MIPA 8, XI MIPA 9, XI IPS 1, XI IPS 2, and XI IPS 3 with a total of 377 students. The sample in this study was selected randomly which was then divided into 2 classes, namely XI MIPA 4 experimental class and XI MIPA 5 control class. The sampling used is cluster random sampling. The results of this research analysis revealed that the independent sample test test obtained post-test data with a value of sig, 0.006 <0.05, which means that there is a difference in the increase in student motivation to learn in the group given treatment or treatment through classical guidance services with the discussion method.

PENGARUH VARIASI DAYA DAN LAMA WAKTU KONTAK LAMPU ULTRAVIOLET TIPE C PADA LEMARI STERILISASI TERHADAP PENURUNAN JUMLAH KUMAN PADA ALAT MAKAN DI KANTIN OFFICE PT.X

The problem of food sanitation hygiene was very important to be addressed, especially in food management facilities such as office canteens. It was found that the number of germs on cutlery in the PT X canteen exceeded the established quality standard, namely 150 colonies/cm2. Attempts to reduce the number of germs on the cutlery of dishes by sterilization using UV-C light. This study aims to determine the variation in power and the length of contact time of ultraviolet lamp type C (UV-C) using a sterilization cabinet against reducing the number of germs on the cutlery at PT.X This type of research is an experiment with a posttest with control design. The cutlery used as a sample was 25 pieces. Data analysis was bivariate statistic analysis. Based on the results, it was known that there was a decrease in the number of germs after UV-C light irradiation was carried out. Irradiation with a power of 15 watts long contact 25 minutes lowers the number of germs 96.89%, Irradiation with a power of 15 watts long contact 30 minutes lowers the number of germs 98.65%, Irradiation with a power of 30 watts long contact 25 minutes lowers the number of germs 99.89%, and Irradiation with a power of 30 watts long contact 30 minutes decreases the number of germs 100%. A decrease in the number of effective germs occurs at a lamp power of 30 watts with a time contact duration of 30 minutes.

Antibacterial Test of Cherry Leaves Ethanol Extract (Muntingia calabura L.) Against Streptococcus mutans

Introduction: Streptococcus mutans is a bacteria that plays an important role in the occurrence of dental caries. Use of antibiotics to treat infections Streptococcus mutans often causes side effects. Cherry leaves (Muntingia calabura L.) contain active compounds that have the potential to have antibacterial effects. This research aims to determine the inhibitory power of cherry leaf ethanol extract against Streptococcus mutans in vitro. Methods: This research uses an experimental method with a post-test-only control group design. Cherry leaf ethanol extract was made by maceration method using 96% ethanol solvent for 5 days. The antibacterial test was carried out using the paper disc diffusion method with varying concentrations of cherry leaf extract, namely 20%, 40%, and 60% w/v dissolved in 10% DMSO. The positive control used was the amoxicillin antibiotic disc, while the negative control used 10% DMSO. Results: The results of the antibacterial test of the ethanol extract of cherry leaves in this study showed that at a concentration of 20% it had an average inhibitory power of 9.16 mm, the extract with a concentration of 40% had an inhibitory power of 11.33 mm, and at a concentration of 60% it had an inhibitory power of 12. 16mm. The positive control amoxicillin had an inhibitory power of 18.67 mm. Conclusion: Cherry leaf ethanol extract has potential as an alternative therapy to overcome Streptococcus mutans bacterial infections.

Backstepping-Based Fuzzy Adaptive Stabilization of Reaction-Diffusion Equation With State Constraints.

This article proposes a stabilization scheme for a cascaded parabolic partial differential equation (PDE)-ordinary differential equation (ODE) system with state constraints. To begin, by employing the fuzzy-logic system (FLS) technique for the unknown nonlinear functions in the ODE subsystem, the influence of the nonlinearities is successfully eliminated. Then, the infinite and finite-dimensional backstepping methods are skillfully applied to the design of control schemes. Specifically, the infinite-dimensional backstepping transformation and its inverse are utilized to obtain a new PDE subsystem, which is convenient for control design. Next, based on the new target PDE-ODE cascade system, a novel first-order filter is subtly introduced into each step of the finite-dimensional backstepping-based controller design procedure to avoid the issue of "explosion of complexity." Furthermore, a novel barrier Lyapunov function (BLF) is constructed to guarantee that the states of the ODE subsystem do not violate the constraints. The controller designed in this article ensures that all signals in the closed-loop system are bounded and the states can converge to zero. Finally, a simulation example verifies that the proposed scheme can achieve satisfactory performance.

Multi-objective branch-and-bound for the design-for-control of water distribution networks with global bounds

This study investigates a design-for-control (DfC) problem formulation for the joint minimization of pressure-induced leakage, maximization of resilience, and minimization of cost in water distribution networks (WDN). The DfC problem, which consists in simultaneously installing new valves and/or pipes and optimizing valve control settings, results in a challenging optimization problem belonging to the class of non-convex multi-objective mixed-integer non-linear programs (MOMINLP). Due to their complex mathematical structure, multi-objective WDN design-for-control problems have previously been solved using general-purpose evolutionary algorithms or local deterministic methods, which do not provide guarantees on the quality of the returned solutions. While branch-and-bound (BB) frameworks have been proposed to approximate the Pareto fronts of MOMINLPs with global bounds, they rely on the availability of attainable solutions which, for WDN design-for-control problems, can be hard to identify. Moreover, in the absence of general-purpose solvers, the performance of multi-objective BB implementations depends, for a given application, on the choice of adequate branching and lower bounding strategies. In this study, we investigate a multi-objective BB algorithm based on tailored branching, lower bounding and additional upper bounding strategies to efficiently approximate the Pareto front of WDN design-for-control problems with bounds of ϵ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\epsilon$$\\end{document}-non-dominance. The proposed algorithm is applied to the optimal DfC of two case study networks and is shown to outperform alternative solution methods.

Neuroadaptive Fault-Tolerant Control Embedded With Diversified Activating Functions With Application to Auto-Driving Vehicles Under Fading Actuation.

This article presents a neuroadaptive fault-tolerant control method for path tracking of multiinput multioutput (MIMO) systems in the presence of modeling uncertainties and external disturbances. In dealing with modeling uncertainties, neural networks (NNs) with diversified activation/basis functions are considered, with which we establish a set of control algorithms that are robust against uncertainties, adaptive to unknown parameters, and tolerant to actuation faults. This is the first work that explicitly takes into account the neural weights uncertainties and activating function uncertainties in multiple layered neural networks in control design. In addition, we apply the developed control algorithms to unmanned ground vehicles (UGVs) with actuator failures. With the aid of Lyapunov stability theory, it is shown that the proposed control is able to drive the vehicle along the desired path with high precision and all the internal signals are uniformly ultimately bounded (UUB) and continuous. Both theoretical analysis and numerical simulation confirm the effectiveness of the designed strategy.

Flying qualities based time-varying stability augmentation system design for tiltrotor conversion control

Tiltrotors have three flight modes that pose control problems and quality defects during the conversion process. To address this, a novel flying qualities-based time-varying stability augmentation system is designed to achieve multi-mode, nonlinear, and time-varying stability. The system integrates a nonlinear time-varying control law with the flying qualities requirements for all three flight modes. It consists of an inner and outer loop control framework, where the control law in the inner loop is designed based on the Lyapunov theorem of stability. The reference models in the outer loop are derived from the flying qualities criteria to meet level one flying qualities requirements. To evaluate the conversion process, a time-varying flying qualities evaluation method is developed, which includes the conversion path, pilot model, and time-varying flying qualities index. The proposed time-varying stability augmentation control system is then tested through simulation during the conversion process. A pilot-aircraft closed-loop system is established for conducting experiments. Comparison between simulation results and pilot-in-loop experiment results demonstrates the effectiveness of the proposed control system. Furthermore, it proves that the evaluation method is suitable for analyzing time-varying systems. This research can be valuable in designing and evaluating stability augmentation controls for strongly time-varying systems.

A Comparative Study of Load Frequency Regulation for Multi-Area Interconnected Grids Using Integral Controller

The present paper provides an optimal design for load frequency control (LFC) in the interconnected power system. To obtain an adequate LFC response alongside shortening implementation time and minimizing costs, an integral (I) controller is used. A deep analysis of the I controller-based LFC is presented. At first, a two-area interconnected power system is used, and to enhance the LFC response, the I controller and frequency bias parameters are optimized using three novel optimization algorithms, which are the incomprehensible but intelligible-in-time logic algorithm (ILA), the coati optimization algorithm (COA), and the brown-bear optimization algorithm (BOA). Also, five well-known techniques, namely, particle swarm optimization (PSO), genetic algorithm (GA), simulated annealing (SA), pattern search (PS), and nonlinear programming (NP), are used. A new objective function utilizing the integral of squared error (ISE), settling time, settling-max, and settling-min of the dynamic response is used to increase the efficacy of estimating the parameters. The presented results in this paper showed that the optimized I controller outperforms the classic I controller. After considering a load change in one area by 18.75%, the optimized I controller achieved the lowest ISE values. ISE values were: 0.00582, 0.00179, 0.00176, 0.00178, 0.00321, 0.00304, 0.00179, 0.00185, and 0.00181, for classic I, PSO-I, GA-I, SA-I, PS-I, NP-I, ILA-I, COA-I, and BOA-I. Then, the proposed method is applied to a nonlinear two-area system, demonstrating that the proposed strategies can deal with nonlinearity. As the purpose of the hybrid power system is to create a robust energy infrastructure that adheres to sustainability standards, the proposed algorithms are analyzed in a three-area multi-source power system comprising renewable energy sources (RESs) such as photovoltaic (PV) and wind turbine (WT), a battery energy storage system (BESS), and an electric vehicle (EV).

Prediction of dredged soil settlement based on improved BP neural network

Based on the measured settlement data from the Reclamation Project of Eastern Hengsha Shoal, two improved BP neural networks optimized by the particle swarm optimization (PSO) algorithm and genetic algorithm (GA) respectively are employed to predict the long-term consolidation settlement of the dredged soil in the reclamation area. By comparing the prediction results of the improved neural networks with those obtained from standard BP neural network and various curve fitting methods including hyperbola method, Hoshino method, and Asaoka method, as well as field-measured data, the improved neural network methods are validated to have a better predictive performance. The error analysis results indicate that compared with the standard BP neural network and curve-fitting prediction methods, the improved BP neural networks exhibit smaller prediction errors in terms of MAE, MSE, RMSE, MAPE, etc., and have a closer match between the predicted settlement values and the actual values. The selected GA-BP and PSO-BP neural network prediction methods in this study demonstrate higher prediction accuracy. Meanwhile, GA-BP demonstrates higher prediction accuracy and generalization ability than PSO-BP, but PSO-BP shows faster convergence in terms of prediction speed. The preferred methods presented in this paper exhibit good robustness and high reliability, which can achieve accurate prediction of dredged soil settlement. Additionally, unlike the traditional curve-fitting methods, the selected methods can effectively reduce the influence of subjective factors during the settlement prediction, and provide a new approach for settlement prediction, which can be effectively utilized as a substitute for long-term settlement monitoring and give reference for the design of settlement control of foundation of further construction projects.