Temperature-Based Fan Speed Optimization Strategy

As energy efficiency and indoor comfort increasingly become key standards in modern residential and office environments,research on intelligent fan speed control systems has become particularly important.This study aims to develop a temperature-feedback-based fan speed optimization strategy to achieve higher energy efficiency and user comfort.Firstly,by analyzing existing fan speed control technologies,their main limitations are identified,such as the inability to achieve smooth speed transitions.To address this issue,a BP-PID speed control algorithm is designed,which dynamically adjusts fan speed based on indoor temperature changes.Experimental validation demonstrates that the designed system can achieve smooth speed transitions compared to traditional fan systems while maintaining stable indoor temperatures.Furthermore,the real-time responsiveness of the system is crucial for enhancing user comfort.Our research not only demonstrates the feasibility of temperature-based fan speed optimization strategies in both theory and practice but also provides valuable insights for energy management in future smart home environments.Ultimately,this research outcome will facilitate the development of smart home systems and have a positive impact on environmental sustainability.

Wind Speed Prediction Using Chicken Swarm Optimization with Deep Learning Model

High precision and reliable wind speed forecasting have become a challenge for meteorologists.Convective events,namely,strong winds,thunderstorms,and tornadoes,along with large hail,are natural calamities that disturb daily life.For accurate prediction of wind speed and overcoming its uncertainty of change,several prediction approaches have been presented over the last few decades.As wind speed series have higher volatility and nonlinearity,it is urgent to present cutting-edge artificial intelligence(AI)technology.In this aspect,this paper presents an intelligent wind speed prediction using chicken swarm optimization with the hybrid deep learning(IWSP-CSODL)method.The presented IWSP-CSODL model estimates the wind speed using a hybrid deep learning and hyperparameter optimizer.In the presented IWSP-CSODL model,the prediction process is performed via a convolutional neural network(CNN)based long short-term memory with autoencoder(CBLSTMAE)model.To optimally modify the hyperparameters related to the CBLSTMAE model,the chicken swarm optimization(CSO)algorithm is utilized and thereby reduces the mean square error(MSE).The experimental validation of the IWSP-CSODL model is tested using wind series data under three distinct scenarios.The comparative study pointed out the better outcomes of the IWSP-CSODL model over other recent wind speed prediction models.

Prediction of Wind Speed Using a Hybrid Regression-Optimization Approach

Predicting wind speed is a complex task that involves analyzing various meteorological factors such as temperature, humidity, atmospheric pressure, and topography. There are different approaches that can be used to predict wind speed, and a hybrid optimization approach is one of them. In this paper, the hybrid optimization approach combines a multiple linear regression approach with an optimization technique to achieve better results. In the context of wind speed prediction, this hybrid optimization approach can be used to improve the accuracy of existing prediction models. Here, a Grey Wolf Optimizer based Wind Speed Prediction (GWO-WSP) method is proposed. This approach is tested on the 2016, 2017, 2018, and 2019 Raw Data files from the Great Lakes Environmental Research Laboratories and the National Oceanic and Atmospheric Administration’s (GLERL-NOAA) Chicago Metadata Archive. The test results show that the implementation is successful and the approach yields accurate and feasible results. The computation time for execution of the algorithm is also superior compared to the existing methods in literature.

Multi-model ensemble forecasting of 10-m wind speed over eastern China based on machine learning optimization

风对人类活动和电力运行有重大影响,准确预报短期风速具有深远的社会和经济意义.基于中国东部100个站点,本研究首先评估了5个业务模式对10米风速的预报能力,日本气象厅JMA模式在减少预报误差方面表现最好.进一步,利用5种数值模式和多种机器学习方法,将动力和统计相结合,对每个站点分别进行了特征工程和机器学习算法优选,建立了10米风速多模式集成预报模型。针对24至96小时预报时长,将该方法的预报性能与基于岭回归的多模式集成和JMA单模式进行比较.结果表明,基于机器学习优选的多模型集成方法可以将JMA模式的预报误差降低39%以上,预报效果的提升在11月最明显.此外,该方法优于基于岭回归的多模式集成方法.

A Whale Optimization Algorithm with Distributed Collaboration and Reverse Learning Ability

Due to the development of digital transformation,intelligent algorithms are getting more and more attention.The whale optimization algorithm(WOA)is one of swarm intelligence optimization algorithms and is widely used to solve practical engineering optimization problems.However,with the increased dimensions,higher requirements are put forward for algorithm performance.The double population whale optimization algorithm with distributed collaboration and reverse learning ability(DCRWOA)is proposed to solve the slow convergence speed and unstable search accuracy of the WOA algorithm in optimization problems.In the DCRWOA algorithm,the novel double population search strategy is constructed.Meanwhile,the reverse learning strategy is adopted in the population search process to help individuals quickly jump out of the non-ideal search area.Numerical experi-ments are carried out using standard test functions with different dimensions(10,50,100,200).The optimization case of shield construction parameters is also used to test the practical application performance of the proposed algo-rithm.The results show that the DCRWOA algorithm has higher optimization accuracy and stability,and the convergence speed is significantly improved.Therefore,the proposed DCRWOA algorithm provides a better method for solving practical optimization problems.

Short-term forecasting optimization algorithms for wind speed along Qinghai-Tibet railway based on different intelligent modeling theories

To protect trains against strong cross-wind along Qinghai-Tibet railway, a strong wind speed monitoring and warning system was developed. And to obtain high-precision wind speed short-term forecasting values for the system to make more accurate scheduling decision, two optimization algorithms were proposed. Using them to make calculative examples for actual wind speed time series from the 18th meteorological station, the results show that: the optimization algorithm based on wavelet analysis method and improved time series analysis method can attain high-precision multi-step forecasting values, the mean relative errors of one-step, three-step, five-step and ten-step forecasting are only 0.30%, 0.75%, 1.15% and 1.65%, respectively. The optimization algorithm based on wavelet analysis method and Kalman time series analysis method can obtain high-precision one-step forecasting values, the mean relative error of one-step forecasting is reduced by 61.67% to 0.115%. The two optimization algorithms both maintain the modeling simple character, and can attain prediction explicit equations after modeling calculation.

Running safety and seismic optimization of a fault-crossing simply-supported girder bridge for high-speed railways based on a train-track-bridge coupling system

Bridges crossing active faults are more likely to suffer serious damage or even collapse due to the wreck capabilities of near-fault pulses and surface ruptures under earthquakes.Taking a high-speed railway simply-supported girder bridge with eight spans crossing an active strike-slip fault as the research object,a refined coupling dynamic model of the high-speed train-CRTS III slab ballastless track-bridge system was established based on ABAQUS.The rationality of the established model was thoroughly discussed.The horizontal ground motions in a fault rupture zone were simulated and transient dynamic analyses of the high-speed train-track-bridge coupling system under 3-dimensional seismic excitations were subsequently performed.The safe running speed limits of a high-speed train under different earthquake levels(frequent occurrence,design and rare occurrence)were assessed based on wheel-rail dynamic(lateral wheel-rail force,derailment coefficient and wheel-load reduction rate)and rail deformation(rail dislocation,parallel turning angle and turning angle)indicators.Parameter optimization was then investigated in terms of the rail fastener stiffness and isolation layer friction coefficient.Results of the wheel-rail dynamic indicators demonstrate the safe running speed limits for the high-speed train to be approximately 200 km/h and 80 km/h under frequent and design earthquakes,while the train is unable to run safely under rare earthquakes.In addition,the rail deformations under frequent,design and rare earthquakes meet the safe running requirements of the high-speed train for the speeds of 250,100 and 50 km/h,respectively.The speed limits determined for the wheel-rail dynamic indicators are lower due to the complex coupling effect of the train-track-bridge system under track irregularity.The running safety of the train was improved by increasing the fastener stiffness and isolation layer friction coefficient.At the rail fastener lateral stiffness of 60 kN/mm and isolation layer friction coefficients of 0.9 and 0.8,respectively,the safe running speed limits of the high-speed train increased to 250 km/h and 100 km/h under frequent and design earthquakes,respectively.

An Adaptive Fruit Fly Optimization Algorithm for Optimization Problems

In this paper, we present a new fruit fly optimization algorithm with the adaptive step for solving unconstrained optimization problems, which is able to avoid the slow convergence and the tendency to fall into local optimum of the standard fruit fly optimization algorithm. By using the information of the iteration number and the maximum iteration number, the proposed algorithm uses the floor function to ensure that the fruit fly swarms adopt the large step search during the olfactory search stage which improves the search speed;in the visual search stage, the small step is used to effectively avoid local optimum. Finally, using commonly used benchmark testing functions, the proposed algorithm is compared with the standard fruit fly optimization algorithm with some fixed steps. The simulation experiment results show that the proposed algorithm can quickly approach the optimal solution in the olfactory search stage and accurately search in the visual search stage, demonstrating more effective performance.

Performance Analysis of Optimization Based FOC and DTC Methods for Three Phase Induction Motor

Three-phase induction motors are becoming increasingly utilized in industrialfield due to their better efficiency and simple manufacture.The speed control of an induction motor is essential in a variety of applications,but it is dif-ficult to control.This research analyses the three-phase induction motor’s perfor-mance usingfield-oriented control(FOC)and direct torque control(DTC)techniques.The major aim of this work is to provide a critical evaluation of devel-oping a simple speed controller for induction motors with improving the perfor-mance of Induction Motor(IM).For controlling a motor,different optimization approaches are accessible;in this research,a Fuzzy Logic Controller(FLC)with Fractional Order Darwinian Particle Swarm Optimization(FODPSO)algorithm is presented to control the induction motor.The FOC and DTC are controlled using FODPSO,and their performance is compared to the traditional FOC and DTC technique.Each scheme had its own simulation model,and the results were com-pared using hardware experimental and MATLAB-Simulink.In terms of time domain specifications and torque improvement,the proposed technique surpasses the existing method.

Geographic Drone-based Route Optimization Approach for Emergency Area Ad-Hoc Network

Wireless sensor Mobile ad hoc networks have excellent potential in moving and monitoring disaster area networks on real-time basis.The recent challenges faced in Mobile Ad Hoc Networks(MANETs)include scalability,localization,heterogeneous network,self-organization,and self-sufficient operation.In this background,the current study focuses on specially-designed communication link establishment for high connection stability of wireless mobile sensor networks,especially in disaster area network.Existing protocols focus on location-dependent communications and use networks based on typically-used Internet Protocol(IP)architecture.However,IP-based communications have a few limitations such as inefficient bandwidth utilization,high processing,less transfer speeds,and excessive memory intake.To overcome these challenges,the number of neighbors(Node Density)is minimized and high Mobility Nodes(Node Speed)are avoided.The proposed Geographic Drone Based Route Optimization(GDRO)method reduces the entire overhead to a considerable level in an efficient manner and significantly improves the overall performance by identifying the disaster region.This drone communicates with anchor node periodically and shares the information to it so as to introduce a drone-based disaster network in an area.Geographic routing is a promising approach to enhance the routing efficiency in MANET.This algorithm helps in reaching the anchor(target)node with the help of Geographical Graph-Based Mapping(GGM).Global Positioning System(GPS)is enabled on mobile network of the anchor node which regularly broadcasts its location information that helps in finding the location.In first step,the node searches for local and remote anticipated Expected Transmission Count(ETX),thereby calculating the estimated distance.Received Signal Strength Indicator(RSSI)results are stored in the local memory of the node.Then,the node calculates the least remote anticipated ETX,Link Loss Rate,and information to the new location.Freeway Heuristic algorithm improves the data speed,efficiency and determines the path and optimization problem.In comparison with other models,the proposed method yielded an efficient communication,increased the throughput,and reduced the end-to-end delay,energy consumption and packet loss performance in disaster area networks.

Optimization on the Impeller of a Low-specific-speed Centrifugal Pump for Hydraulic Performance Improvement

In order to widen the high-efficiency operating range of a low-specific-speed centrifugal pump, an optimization process for considering efficiencies under 1.0Qd and 1.4Qd is proposed. Three parameters, namely, the blade outlet width b2, blade outlet angle β2, and blade wrap angle φ, are selected as design variables. Impellers are generated using the optimal Latin hypercube sampling method. The pump efficiencies are calculated using the software CFX 14.5 at two operating points selected as objectives. Surrogate models are also constructed to analyze the relationship between the objectives and the design variables. Finally, the particle swarm optimization algorithm is applied to calculate the surrogate model to determine the best combination of the impeller parameters. The results show that the performance curve predicted by numerical simulation has a good agreement with the experimental results. Compared with the efficiencies of the original impeller, the hydraulic efficiencies of the optimized impeller are increased by 4.18% and 0.62% under 1.0Qd and 1.4Qd, respectively. The comparison of inner flow between the original pump and optimized one illustrates the improvement of performance. The optimization process can provide a useful reference on performance improvement of other pumps, even on reduction of pressure fluctuations.

Speed profile optimization of catenary-free electric trains with lithium-ion batteries

Catenary-free operated electric trains, as one of the recent technologies in railway transportation, has opened a new field of research: speed profile optimization and energy optimal operation of catenary-free operated electric trains. A well-formulated solution for this problem should consider the characteristics of the energy storage device using validated models and methods. This paper discusses the consideration of the lithium-ion battery behavior in the problem of speed profile optimization of catenary-free operated electric trains. We combine the single mass point train model with an electrical battery model and apply a dynamic programming approach to minimize the charge taken from the battery during the catenary-free operation. The models and the method are validated and evaluated against experimental data gathered from the test runs of an actual battery-driven train tested in Essex, UK. The results show a significant potential in energy saving. Moreover, we show that the optimum speed profiles generated using our approach consume less charge from the battery compared to the previous approaches.

Position Control Optimization of Aerodynamic Brake Device for High-speed Trains

The aerodynamic braking is a clean and non-adhesion braking, and can be used to provide extra braking force during high-speed emergency braking. The research of aerodynamic braking has attracted more and more attentions in recent years. However, most researchers in this field focus on aerodynamic effects and seldom on issues of position control of the aerodynamic braking board. The purpose of this paper is to explore position control optimization of the braking board in an aerodynamic braking prototype. The mathematical models of the hydraulic drive unit in the aerodynamic braking system are analyzed in detail, and the simulation models are established. Three control functions--constant, linear, and quadratic--are explored. Two kinds of criteria, including the position steady-state error and the acceleration of the piston rod, are used to evaluate system performance. Simulation results show that the position steady state-error is reduced from around 12-2 mm by applying a linear instead of a constant function, while the acceleration is reduced from 25,71-3.70 m/s2 with a quadratic control function. Use of the quadratic control function is shown to improve system performance. Experimental results obtained by measuring the position response of the piston rod on a test-bench also suggest a reduced position error and smooth movement of the piston rod. This implies that the acceleration is smaller when using the quadratic function, thus verifying the effectiveness of control schemes to improve to system performance. This paper proposes an effective and easily implemented control scheme that improves the position response of hydraulic cylinders during position control.

Speed Control of Motor Based on Improved Glowworm Swarm Optimization

To better regulate the speed of brushless DC motors,an improved algorithm based on the original Glowworm Swarm Optimization is proposed.The proposed algorithm solves the problems of poor robustness,slow convergence,and low accuracy exhibited by traditional PID controllers.When selecting the glowworm neighborhood set,an optimization scheme based on the growth and competition behavior of weeds is applied to a single glowworm to prevent falling into a local optimal solution.After the glowworm’s position is updated,the league selection operator is introduced to search for the global optimal solution.Combining the local search ability of the invasive weed optimization with the global search ability of the league selection operator enhances the robustness of the algorithm and also accelerates the convergence speed of the algorithm.The mathematical model of the brushless DC motor is established,the PID parameters are tuned and optimized using improved Glowworm Swarm Optimization algorithm,and the speed of the brushless DC motor is adjusted.In a Simulink environment,a double closed-loop speed control model was established to simulate the speed control of a brushless DC motor,and this simulation was compared with a traditional PID control.The simulation results show that the model based on the improved Glowworm Swarm Optimization algorithm has good robustness and a steady-state response speed for motor speed control.

A Practical Speed Loss Prediction Model at Arbitrary Wave Heading for Ship Voyage Optimization

This paper proposes a semi-empirical model to predict a ship’s speed loss at arbitrary wave heading.In the model,the formulas that estimate a ship’s added resistance due to waves attacking from different heading angles have been further developed.A correction factor is proposed to consider the nonlinear effect due to large waves in power estimation.The formulas are developed and verified by model tests of 5 ships in regular waves with various heading angles.The full-scale measurements from three different types of ships,i.e.,a PCTC,a container ship,and a chemical tanker,are used to validate the proposed model for speed loss prediction in irregular waves.The effect of the improved model for speed loss prediction on a ship’s voyage optimization is also investigated.The results indicate that a ship’s voyage optimization solutions can be significantly affected by the prediction accuracy of speed loss caused by waves.

Length optimization of straight line connecting turnout on main line in high-speed railway station yard

Taking the development of high-speed railway in China as background, and referring to the dynamic theory and wheel-rail contact mode, dynamic analysis model was established, considering the setting position of straight lines and running conditions of train in high-speed railway station yard. Using the established model, and choosing vehicle lateral acceleration and wheel suspension as the evaluation indexes, dynamic characteristic of vehicle traveling in turnout and adjacent area on main line was analyzed, and effects on travelling safety and stability of train aroused by length variation of straight lines were calculated based on analyzing the damping rules of vibration. The results show that, a certain length of straight lines can alleviate the vibration aroused in turnout and curve(turnout), length of straight lines connecting turnouts in different sections on main line was proposed to meet the demand of traveling stability, and shortening or cancelation of straight line for the scale limitation of station yard has less influence on operation safety of train.

TOOL PATH OPTIMIZATION OF POCKET CORNER

In milling around sharp corners, residual materials are left at sharp corners when the stepover is extremely long in the contour-parallel tool path. Milling force at the sharp corner rises momentarily due to the increase of the cutter contact length, thus shortening the tool life and leading to machine chatter, even cutter breakage. Then a tool path improvement method by inserting biarc transition segments in the contour-parallel tool path is proposed for milling the pocket. Using the method, the cutter moves along the biarc transition tool path. And the corner material is removed. The improved tool path is continuous for clearing residual materials at the sharp corner. Finally, the machining experiment validates the proposed method.

OPTIMAL CONTROL OF AN ACTIVE SUSPENSION SYSTEMEMPLOYING HIGH SPEED ON/OFF SOLENOID VALVE

Previous studies have confirmed that an active suspension system with high speed ON/OFF solenoid valves could provide the same vibration isolation efficiency as that of system with pressure proportional valve. In this study, by using Linear-quadratic optimization technique and Kalman filter method, an optimal regulator controller with a state observer was designed for the proposed system. Simulation and experimental research was conducted on a quarter car model. The simulation analysis of the system frequency characteristic suggested that the peak value of magnitude response curve in the case of system with an optimal controller would be lowered significantly, and the experiment results also showed that an improvement in the vibration isolation effect was obtained in using the designed optimal controller over the sky hook damper controller.

Optimal Control of Hydraulic Position System Employing High Speed On/Off Solenoid Valve

A hydraulic position system was designed employing two high speed On/Off solenoid valves with PWM(Pulse width modulation) technique and using LQ(Linear Quadratic) optimization principle. Based on the system, the parts of system can be formulated with equations. According to equations, the mathematical model of the system was established. By simulation, the corresponding LQ optimal controller was designed and the PWM signals were generated. The comparison of the simulation and experiment results show that LQ optimal control method with PWM technique employing high speed On/Off solenoid valve can provide better system performance and a high position precision is obtained.

Development of CAD/CAM system and profile measuring device for CNC grinding machine to obtain an optimal grinding speed

Cam mechanics is one of the most popular devices for generating irregular motions and is widely used in automatic equipment,such as textile machines,internal combustion engines,and other automatic devices.In order to obtain a positive motion from the follower using a rotating cam,its shape should be correctly designed and manufactured.The development of an adequate CAD/CAM system for a cam profile CNC grinding machine is necessary to manufacture high-precision cams.The purpose of this study is the development of a CAD/CAM system and profile measuring device for a CNC grinding machine to obtain an optimal grinding speed with a constant surface roughness.Three types of disk cams were manufactured using the proposed algorithm and procedures to verify effectiveness of the developed CAD/CAM system.