Intervention in the social population space of Cultural Algorithm

Cultural Algorithms (CA) offers a better way to simulate social and culture driven agents by introducing the notion of culture into the artificial population. When it comes to mimic intelligent social beings such as humans, the search for a better fit or global optima becomes multi dimensional because of the complexity produced by the relevant system parameters and intricate social behaviour. In this research an extended CA framework has been presented. The architecture provides extensions to the basic CA framework. The major extensions include the mechanism of influencing selected individuals into the population space by means of existing social network and consequently alter the cultural belief favourably. Another extension of the framework was done in the population space by introducing the concept of social network. The agents in the population are put into one (or more) network through which they can communicate and propagate knowledge. Identification and exploitation of such network is necessary sinceit may lead to a quicker shift of the cultural norm

Optimizing artificial neural networks using LevyChaotic mapping on Wolf Pack optimization algorithm for detect driving sleepiness

Artificial Neural Networks (ANNs) are utilized to solve a variety of problems in many domains. In this type of network, training and selecting parameters that define networks architecture play an important role in enhancing the accuracy of the network's output; Therefore, Prior to training, those parameters must be optimized. Grey Wolf Optimizer (GWO) has been considered one of the efficient developed approaches in the Swarm Intelligence area that is used to solve real-world optimization problems. However, GWO still faces a problem of the slump in local optimums in some places due to insufficient diversity. This paper proposes a novel algorithm Levy Flight- Chaotic Chen mapping on Wolf Pack Algorithm in Neural Network. It efficiently exploits the search regions to detect driving sleepiness and balance the exploration and exploitation operators, which are considered implied features of any stochastic search algorithm. Due to the lack of dataset availability, a dataset of 15 participants has been collected from scratch to evaluate the proposed algorithm's performance. The results show that the proposed algorithm achieves an accuracy of 99.3%

System Identification And Control Of Automatic Car Pedal Pressing System For Low-Speed Driving In A Road Traffic Delay

Congestion in major cities has been a typical occurrence among communities. Being stuck in traffic for hours in a sitting position necessitates recurrent chores of manually pressing the accelerator and stop pedals excessively, which, if performed without the proper sitting posture, can result in quick weariness, especially for the driver's leg and back. Therefore, this research is to automate the pressing mechanism by modelling an actuator for pedals pressing concentrating for low-speed driving in a road traffic delay. This project presents system identification and control of automatic car pedal pressing system for low-speed driving in a road traffic delay. Two parameters such as force and low speed will be observed for both controllers and the ability to attenuate disturbance will be simulated. Output of the controller will determine the force of the car brake. The parallel linkage is connected to the actuator such that it provides an opposite reaction to the car pedal. The system identification is taken from the dynamic behavior of the system and modelled using input-output data acquired directly from the experimental rig. The work utilized a neural network to model the system as the system exhibits highly nonlinear behavior. This paper compares the low-speed control with both controllers: conventional PID and fuzzy logic controller with respect to overshoot and steady state error. A PID controller and a Fuzzy controller were designed, simulated, and compared in their ability to control the speed of the car. Both controllers were then implemented and tested in automatic car pedal pressing system. The controller gains were tuned using metaheuristic algorithm which is Particle Swarm Algorithm (PSO) for optimal values of fuzzy controller parameters. The controller parameters are optimized based on Integral Squared Error (ISE), Integral Absolute Error (IAE), Integral Time Absolute Error (ITAE) and Mean Squared Error) MSE. The comparative assessment of both controllers was reported and discussed. It shown that Fuzzy logic controller performs better than PID controller with 1.2724% reduction in steady state error and 3.64% in overshoot respectively

DETECTION PROCESS OF ENERGY LOSS IN ELECTRIC RAILWAY VEHICLES

The paper deals with the detection process of energy loss in electric railway hauling vehicles. The importance of efficient energy use in railways and cost-effective rail transport tendency toward regenerative braking energy are considered. In addition, the current situation and improvement opportunities to achieve efficient energy use are examined. Seven measurement series were performed with scheduled Railjet trains between Hegyeshalom and Győr railway stations in Hungary. This railway section is related to the Hungarian State Railways' No. 1 main railway line (between Budapest-Kelenföld and Hegyeshalom state board), which is a part of the international railway line between Budapest and Vienna (capitals of Hungary and Austria, respectively). This double-track, electrified railway line with traditional ballasted superstructures and continuously welded rail tracks is important due to the international passenger and freight transport between Germany, Austria, and Hungary. The value of the regenerative braking energy can be even 20-30% of the total consumed energy. This quite enormous untapped energy can be used for several aims, e.g., for comfort energy demand (air conditioning, heating-cooling, lighting, etc.) or energy-intensive starts. The article also investigates the optimization of regenerative braking energy by seeking the energy-waste locations and the reasons for the significant consumption. The train operator's driving style and habit have been identified as one of the main reasons. Furthermore, train driver assistance systems are recommended to save energy, which is planned for future research

A Comparative and Analytical Review of Iot-Enabled Smart Accidental Management Systems

One of the most important issues that emerging nations are addressing is road accidents. It is important to develop smart accidental management systems with low cost and efforts to prevent accidents and causalities. The amalgamation of Intelligent Transportation Systems (ITS) and Information and Communications Technology (ICT) is expected to dramatically change how people experience driving by enabling cutting-edge traffic monitoring and incident detection strategies. This analysis focuses on various components of SAMS, such as sensor networks, communication protocols, data processing techniques, and decision-making algorithms. It examines how these components work together to create a connected infrastructure capable of detecting and responding to accidents promptly. The review highlights the role of data analytics in enhancing accident prediction and prevention. By processing and analyzing enormous real-time data from cameras, sensors, and other sources, IoT-driven SAMS can identify patterns and anomalies, allowing for proactive measures to avoid accidents in various settings, including transportation, industries, and public spaces

Rollover warning system for tractor-semitrailer using a modified odenthal rollover index algorithm

Any accident involving a tractor-semitrailer could significantly affect life and component damage as well as the surrounding environment due to the size of the vehicle. One of the main factors that causes tractor-semitrailer accidents is vehicle rollover instability. Therefore, this study aimed to develop a vehicle instability avoidance system for a tractor-semitrailer by implementing it on an accurate tractorsemitrailer model. In developing the model, a new approach was proposed by adopting a virtual Pacejka tire model in modelling the hitch joint of the tractor-semitrailer. The virtual Pacejka tire model has included a 16 degree-of-freedom tractor-semitrailer within MATLAB/Simulink software and later verified using the TruckSim model and validated with published data. It is observed from the verification and validation results, the tractor-semitrailer model using the virtual Pacejka tire model for the hitch joint showed a similar response to the behaviour of the TruckSim model and published data. In terms of vehicle instability avoidance system, the fastest response of the tractor-semitrailer rollover index based on early warning indicator was selected by utilizing several types of rollover index algorithm proposed by the previous researchers. The step steering manoeuvres simulation at a various speed was conducted using MATLAB/Simulink software to obtain the rollover index. It can be observed from the results that the rollover index algorithm proposed by Odenthal provides the fastest index based on the early warning indicator on the tractor unit. In order to optimise the rollover index performance, the Odenthal rollover index algorithm was modified and optimised using Particle Swarm Optimisation (PSO). Finally, the rollover index algorithm was proposed by integrating the modified Odenthal rollover index algorithm with driver steering and vehicle speed inputs instead of lateral acceleration. The modified Odenthal rollover index algorithm performance was evaluated by conducting an experiment involving the step steering manoeuvres, subjected to various vehicle speeds and load conditions through the Hardware-in-the- Loop (HIL) simulation in the TruckSim driving simulator and MATLAB/Simulink software. It was observed from the experimental results that the modified Odenthal rollover index algorithm produced 12.4% faster Time-To-Warn (TTW) than the Odenthal rollover index for the driver. Thus, the modified Odenthal rollover index algorithm demonstrated a better early warning system for the driver to initiate the corrective action

Determining Additional Modulus of Subgarde Reaction Based on Tolerable Settlement for the Nailed-slab System Resting on Soft Clay.

Abstract—Nailed-slab System is a proposed alternative solution for rigid pavement problem on soft soils. Equivalent modulus of subgrade reaction (k’) can be used in designing of nailed-slab system. This modular is the cumulative of modulus of subgrade reaction from plate load test (k) and additional modulus of subgrade reaction due to pile installing (∆∆∆∆k). A recent method has used reduction of pile resistance approach in determining ∆∆∆∆k. The relative displacement between pile and soils, and reduction of pile resistance has been identified. In fact, determining of reduction of pile resistance is difficult. This paper proposes an approach by considering tolerable settlement of rigid pavement. Validation is carried out with respect to a loading test of nailed-slab models. The models are presented as strip section of rigid pavement. The theory of beams on elastic foundation is used to calculate the slab deflection by using k’. Proposed approach can results in deflection prediction close to observed one. In practice, the Nailed-slab System would be constructed by multiple-row piles. Designing this system based on one-pile row analysis will give more safety design and will consume less time

Multi-Agent Systems

A multi-agent system (MAS) is a system composed of multiple interacting intelligent agents. Multi-agent systems can be used to solve problems which are difficult or impossible for an individual agent or monolithic system to solve. Agent systems are open and extensible systems that allow for the deployment of autonomous and proactive software components. Multi-agent systems have been brought up and used in several application domains