Artificial immune system based on adaptive clonal selection for feature selection and parameters optimisation of support vector machines

Artificial immune system (AIS) algorithm based on clonal selection method can be defined as a soft computing method inspired by theoretical immune system in order to solve science and engineering problems. Support vector machine (SVM) is a popular pattern classification method with many diverse applications. Kernel parameter setting in the SVM training procedure along with the feature selection significantly impacts on the classification accuracy rate. In this study, AIS based on Adaptive Clonal Selection (AISACS) algorithm has been used to optimise the SVM parameters and feature subset selection without degrading the SVM classification accuracy. Several public datasets of University of California Irvine machine learning (UCI) repository are employed to calculate the classification accuracy rate in order to evaluate the AISACS approach then it was compared with grid search algorithm and Genetic Algorithm (GA) approach. The experimental results show that the feature reduction rate and running time of the AISACS approach are better than the GA approach.     

Networked LQG control over lossy channels with computational/packet-transmission delays and coarsely quantised packets

This article addresses the linear quadratic Gaussian (LQG) control problem of networked multi-input, multi-output systems where computational delay exists and the measurement and control signals are packetised and transmitted through a network within which random delay and packet loss may occur during transmissions. A transmission control protocol (TCP)-like protocol for the communication network is considered in which acknowledgement is sent from the actuator to the controller if and only if the control packet is received, assuming these acknowledgements always reach the estimator in time and without fail. To minimise the data word-length for transmissions over the network and to maximise control system performance, it is proposed that different quantisation resolutions be used for transmission data encapsulation, and control and output signals A/D-D/A conversions at sensor/actuator. To circumvent the problem of disparity between encapsulation and A/D-D/A quantisation resolutions, a pseudo-stochastic approach via subtractive dither is applied to quantise the transmission packets. This also enables us to model the quantisation errors as uncorrelated independent zero-mean additive white noises and apply standard LQG methodology and separation principle to design the estimator and the controller separately. An example is included to demonstrate the effectiveness of the approach.     

Attention control learning in the decision space using state estimation

The main goal of this paper is modelling attention while using it in efficient path planning of mobile robots. The key challenge in concurrently aiming these two goals is how to make an optimal, or near-optimal, decision in spite of time and processing power limitations, which inherently exist in a typical multi-sensor real-world robotic application. To efficiently recognise the environment under these two limitations, attention of an intelligent agent is controlled by employing the reinforcement learning framework. We propose an estimation method using estimated mixture-of-experts task and attention learning in perceptual space. An agent learns how to employ its sensory resources, and when to stop observing, by estimating its perceptual space. In this paper, static estimation of the state space in a learning task problem, which is examined in the Webots^TM simulator, is performed. Simulation results show that a robot learns how to achieve an optimal policy with a controlled cost by estimating the state space instead of continually updating sensory information.     

A dynamic multi-plant lot-sizing and distribution problem

In this paper, we investigate a multi-plant, production planning and distribution problem for the simultaneous optimisation of production, inventory control, demand allocation and distribution decisions. The objective of this rich problem is to satisfy the dynamic demand of customers while minimising the total cost of production, inventory and distribution. By solving the problem, we determine when the production needs to occur, how much has to be produced in each of the plants, how much has to be stored in each of the warehouses and how much needs to be delivered to each customer in each period. On a large real data-set inspired by a case obtained from an industrial partner, we show that the proposed integration is highly effective. Moreover, we study several trade-offs in a detailed sensitivity analysis. Our analyses indicate that the proposed scenarios give the company competitive advantage in terms of reduced total logistics cost, and also highlight more possibilities that become available taking advantage of an integrated approach towards logistics planning. These abundant opportunities are to be synergised and exploited in an interconnected open global logistics system.     

Antioxidative enzyme activity and internal browning of 1‐methylcyclopropene‐treated European pear fruits (cv. ‘Shahmiveh’ and ‘Sebri’)

The effects of 1‐methylcyclopropene (1‐MCP) on antioxidative enzyme and internal browning (IB) incidence of two European pear cultivars ‘Shahmiveh’ and ‘Sebri’ stored at 0.5 °C were investigated. Ethylene production of ‘Sebri’ was delayed by 1‐MCP but suppressed in ‘Shahmiveh’. IB increased in both cultivars, with a higher level of the incidence in ‘Shahmiveh’, and was reduced by 1‐MCP. Activities of catalase (CAT) and peroxidase, but not superoxide dismutase (SOD), decreased in untreated fruit during the first 40 days. 1‐MCP had little effect on SOD activity or on total phenolics. Polyphenoloxidase activity did not increase over time in 1‐MCP‐treated fruit of the IB sensitive ‘Shahmiveh’, and the effect was inconsistent for ‘Sebri’. Ascorbic acid (AA) levels in 1‐MCP‐treated fruit of both cultivars declined at a lower rate compared with untreated fruit during storage, but the reduction in AA levels was faster in ‘Shahmiveh’ compared with ‘Sebri’. Also, the effects of 1‐MCP on antioxidative systems may be related to IB development.