Multi-agent reinforcement learning for route guidance system

Nowadays, multi-agent systems are used to create applications in a variety of areas, including economics, management, transportation, telecommunications, etc. Importantly, in many domains, the reinforcement learning agents try to learn a task by directly interacting with its environment. The main challenge in route guidance system is to direct vehicles to their destination in a dynamic traffic situation, with the aim of reducing travel times and ensuring efficient use of available road network capacity. This paper proposes a multi-agent reinforcement learning algorithm to find the best and shortest path between the origin and destination nodes. The shortest path such as the lowest cost is calculated using multi-agent reinforcement learning model and it will be suggested to the vehicle drivers in a route guidance system. The proposed algorithm has been evaluated based on Dijkstra's algorithm to find the optimal solution using Kuala Lumpur (KL) road network map. A number of route cases have been used to evaluate the proposed approach based on the road network problems. Finally, the experiment results demonstrate that the proposed approach is feasible and efficient

The dominant of Bloggers in Malaysian politics through social networks

Every country in this world has own political issues. In Malaysia for example, political issues played an important role that can influence other factors such as social and economy. As we all know, political factor can give positive and negative effect to a situation in Malaysia. The frequent usage of computer nowadays by Malaysian people helps in spreading information and news about political situation in Malaysia through cyberspace. In this paper, we use web mining system with Artificial Immune System (AIS) to regain a small group of relevant websites and webpages on political issues in Malaysia. To analyze the relationship between website and webpages, the concept of social networks will be used. Result from the web mining system with AIS will be used to understand the impact of social network to the political situation in Malaysia

BATTERY SAFETY SYSTEM IN ENERGY LOAD USAGE OF ELECTRIC CAR

Battery Safety system in energy load usage of electric car with current sensor ACS 712 as measure continuous flow on accu voltage divider and voltage sensor to measure to the level of the voltage on the sensors, both accu serves to measure the capacity of energy used and stored on the accu. The method used is to conduct research and utilize data to accu capacity in energy capacity on electric cars. On the tools side, there is a security detector device accu as an energy source in electric cars, according to the current sensor value ACS712 and circuit Voltage Diveder that serves to provide an analog voltage signal as signal data input into Microcontroller ATMega32 that serves to convert that data into the energy management system. The ATMega32 microcontroller is used as a data processing unit that will do data processing process voltage and current continuously while being given a burden. The results obtained is to give an indication of the form of the alarm using a buzzer when the conditions of energy at electric cars under level 50%. then decide and connect the load BLDC Motor via Relays burden on electric car if the battery is not sufficient energy capacity required electric car

Design and performance analysis of cooling tower

Cooling towers are widely used to dissipate process waste heat into the atmosphere. Based on the direct contact of two of the earth’s most common substances : air and wate

Analysis of Transient Response for Coupled Tank System via Conventional and Particle Swarm Optimization (PSO) Techniques

This paper investigates the implementation of conventional and Particle Swarm Optimization (PSO) techniques to obtain optimal parameters of controller. In this research, the transient responses of the Coupled Tank System (CTS) are analyzed with the various conventional and metaheuristic techniques which are Trial and Error, Auto-Tuning, Ziegler-Nichols (ZN), Cohen-Coon (CC), standard PSO and Priority-based Fitness PSO (PFPSO) to tune the PID controller parameters. The purpose of this research is to maintain the liquid at the specific or required height in the tank. Simulation is conducted within Matlab environment to verify the performance of the system in terms of Settling Time (Ts), Steady State Error (SSE) and Overshoot (OS). It has been demonstrated that implementation of meta-heuristic techniques are potential approach to control the desired liquid level and improve the system performances

An H∞ design for dynamic pricing in the smart grid.

An H∞ design for dynamic pricing in the smart grid is proposed. This design jointly considers the operation of a distribution network operator and a market operator. In the design, a ratio of the regulated output energy to the disturbance energy is minimized to address the worst-case scenario. Linear matrix inequality approaches are used to formulate the design problem as a convex problem. Fuzzy interpolation techniques are integrated into the design procedure so that nonlinear grid dynamics can be addressed. In contrast with existing designs, the proposed design can yield a more reliable and practical pricing scheme as shown via simulations

An H∞ design for dynamic pricing in the smart grid

An H∞ design for dynamic pricing in the smart grid is proposed. This design jointly considers the operation of a distribution network operator and a market operator. In the design, a ratio of the regulated output energy to the disturbance energy is minimized to address the worst-case scenario. Linear matrix inequality approaches are used to formulate the design problem as a convex problem. Fuzzy interpolation techniques are integrated into the design procedure so that nonlinear grid dynamics can be addressed. In contrast with existing designs, the proposed design can yield a more reliable and practical pricing scheme as shown via simulations

Clustering of Indonesian forest fires using self organizing maps

This paper focuses on clustering the locations of Indonesian forest fires and visualizing them into a two-dimensional map using a self-organizing map (SOM) algorithm. The input data is based on the quantity of the hot spots of forest fires that spread in several locations within ten months period. We analyze the distributions of the hot spots locations of the regions that may have the high frequencies to risk of the forest fires disaster using the SOM algorithm. We have used a principal component analysis (PCA) to reduce the size of the original datasets in order to improve the accuracy of the clustering results. The SOM algorithm has been used to cluster and visualize the map of the hot spots locations into four groups based on the relative similarity of the risks of forest fires on each of the regions such as danger level, low level, high risks, and low risks. From the analysis we have found that a time period where the highest level of quantity and intensity of the forest fires occurs in some regions can be clearly classified

Route selection of mobile agent for query retrieval using GA

Mobile agents often have a task to collect data from several predefined sites. This should be done in an efficient way by minimizing the elapsed time. Usually these agents only know the list of sites but not the distances between them. This paper proposes a method to minimize a network routing time taken by the mobile agents to collect information from different sites using genetic algorithm (GA). The mobile agents repeat travelling over short routes and avoid longer ones. Mobile agents for query retrieval have used the GA to select the best routes that minimize the query retrieval time. The result shows that the proposed method provides good time minimization in retrieving the query results by the mobile agents based on different GA parameters

Web mining for Malaysia’s political social networks using artificial immune system

Currently, politic is one of the critical and hot issues in Malaysia. There are many aspects that are related with politics. These politic aspects are mainly about spreading rumors and information through cyberspace that created positive and negative effects to the political situations in Malaysia. There are many branches of cyberspace that can be used by the Internet users to channel their opinions such as websites, forums and blogs which contain the political issues in Malaysia. In this paper, we have analyzed an adaptive model of web mining using Artificial Immune System (AIS) to retrieve the list of URLs that have relevant information on political issues in Malaysia. In addition, we have also used a concept of social network analysis in order to understand the relationships among the websites and web pages related to the political issues in Malaysia. The results from this model have been used to analyze the social networks and the impact of online community which contribute to the outcome of Malaysia's 12th general election