Optimizing mixture properties of biodiesel production using genetic algorithm-based evolutionary support vector machine

Nowadays, biodiesel is used as one of the alternative renewable energy due to the increasing energy demand. However, optimum production of biodiesel still requires a huge number of expensive and time-consuming laboratory tests. To address the problem, this research develops a novel Genetic Algorithm-based Evolutionary Support Vector Machine (GA-ESIM). The GA-ESIM is an Artificial Intelligence (AI)-based tool that combines K-means Chaotic Genetic Algorithm (KCGA) and Evolutionary Support Vector Machine Inference Model (ESIM). The ESIM is utilized as a supervised learning technique to establish a highly accurate prediction model between the input--output of biodiesel mixture properties; and the KCGA is used to perform the simulation to obtain the optimum mixture properties based on the prediction model. A real biodiesel experimental data is provided to validate the GA-ESIM performance. Our simulation results demonstrate that the GA-ESIM establishes a prediction model with better accuracy than other AI-based tool and thus obtains the mixture properties with the biodiesel yield of 99.9%, higher than the best experimental data record, 97.4%.     

The practice and challenges of solid waste management in Singapore

This paper presents an overview of the current solid waste management situation in Singapore and provides a brief discussion of the future challenges. Singapore is a small island city-state with a large population, warm climate and high humidity. Over the past two to three decades, rapid industrialization and economic development have caused a tremendous increase in solid waste generation. The yearly disposed solid waste increased from 0.74 million tonnes in 1972 to 2.80 million tonnes in 2000. Solid waste management in Singapore has traditionally been undertaken by the Ministry of Environment (ENV), with the participation of some private sectors in recent years. The hierarchy of solid waste management in Singapore is waste minimization (reduce, reuse and recycle or so-called 3 Rs), followed by incineration and landfill. As land is extremely scarce and only one newly constructed offshore landfill site is available, solid waste incineration has been identified as the most preferred disposal method. Waste minimization, the utilization of incineration ashes, industrial waste management are regarded to be the major challenges in the future.